# -*- coding: utf-8 -*-
from django.conf import settings
-from lucene import SimpleFSDirectory, IndexWriter, CheckIndex, \
+from django.dispatch import Signal
+from lucene import SimpleFSDirectory, NIOFSDirectory, IndexWriter, IndexReader, IndexWriterConfig, CheckIndex, \
File, Field, Integer, \
NumericField, Version, Document, JavaError, IndexSearcher, \
QueryParser, PerFieldAnalyzerWrapper, \
# KeywordAnalyzer
# Initialize jvm
-JVM = initVM(CLASSPATH)
+JVM = initVM(CLASSPATH, maxheap=settings.JVM_MAXHEAP)
import sys
import os
import errno
from librarian import dcparser
from librarian.parser import WLDocument
+from lxml import etree
import catalogue.models
+from pdcounter.models import Author as PDCounterAuthor, BookStub as PDCounterBook
from multiprocessing.pool import ThreadPool
from threading import current_thread
+from itertools import chain
import atexit
import traceback
-
+import logging
+log = logging.getLogger('search')
class WLAnalyzer(PerFieldAnalyzerWrapper):
def __init__(self):
"""
def __init__(self):
self.make_index_dir()
- self.store = SimpleFSDirectory(File(settings.SEARCH_INDEX))
+ self.store = NIOFSDirectory(File(settings.SEARCH_INDEX))
def make_index_dir(self):
try:
pass
else: raise
+ def close(self):
+ self.store.close()
+
class IndexChecker(IndexStore):
def __init__(self):
"""
SNIPPET_DIR = "snippets"
- def __init__(self, book_id):
+ def __init__(self, book_id, revision=None):
try:
os.makedirs(os.path.join(settings.SEARCH_INDEX, self.SNIPPET_DIR))
except OSError as exc:
pass
else: raise
self.book_id = book_id
+ self.revision = revision
self.file = None
+ @property
+ def path(self):
+ if self.revision: fn = "%d.%d" % (self.book_id, self.revision)
+ else: fn = "%d" % self.book_id
+
+ return os.path.join(settings.SEARCH_INDEX, self.SNIPPET_DIR, fn)
+
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)
+
+ if 'w' in mode:
+ if os.path.exists(self.path):
+ self.revision = 1
+ while True:
+ if not os.path.exists(self.path):
+ break
+ self.revision += 1
+
+ self.file = open(self.path, mode)
self.position = 0
return self
"""Close snippet file"""
self.file.close()
+ def remove(self):
+ self.revision = None
+ try:
+ os.unlink(self.path)
+ self.revision = 0
+ while True:
+ self.revision += 1
+ os.unlink(self.path)
+ except OSError:
+ pass
+
class BaseIndex(IndexStore):
"""
analyzer = WLAnalyzer()
self.analyzer = analyzer
- def open(self, analyzer=None):
+ def open(self, timeout=None):
if self.index:
raise Exception("Index is already opened")
- self.index = IndexWriter(self.store, self.analyzer,\
- IndexWriter.MaxFieldLength.LIMITED)
+ conf = IndexWriterConfig(Version.LUCENE_34, self.analyzer)
+ if timeout:
+ conf.setWriteLockTimeout(long(timeout))
+ self.index = IndexWriter(self.store, conf)
return self.index
def optimize(self):
try:
self.index.optimize()
except JavaError, je:
- print "Error during optimize phase, check index: %s" % je
+ log.error("Error during optimize phase, check index: %s" % je)
self.index.close()
self.index = None
+ index_changed.send_robust(self)
+
+ super(BaseIndex, self).close()
+
def __enter__(self):
self.open()
return self
self.close()
+index_changed = Signal()
+
+
class Index(BaseIndex):
"""
Class indexing books.
def __init__(self, analyzer=None):
super(Index, self).__init__(analyzer)
- def index_tags(self):
+ def index_tags(self, *tags, **kw):
"""
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)
+ remove_only = kw.get('remove_only', False)
+ # first, remove tags from index.
+ if tags:
+ q = BooleanQuery()
+ for tag in tags:
+ b_id_cat = BooleanQuery()
- for tag in catalogue.models.Tag.objects.all():
- doc = Document()
- doc.add(NumericField("tag_id", Field.Store.YES, True).setIntValue(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)
+ q_id = NumericRangeQuery.newIntRange("tag_id", tag.id, tag.id, True, True)
+ b_id_cat.add(q_id, BooleanClause.Occur.MUST)
+
+ if isinstance(tag, PDCounterAuthor):
+ q_cat = TermQuery(Term('tag_category', 'pd_author'))
+ elif isinstance(tag, PDCounterBook):
+ q_cat = TermQuery(Term('tag_category', 'pd_book'))
+ else:
+ q_cat = TermQuery(Term('tag_category', tag.category))
+ b_id_cat.add(q_cat, BooleanClause.Occur.MUST)
+
+ q.add(b_id_cat, BooleanClause.Occur.SHOULD)
+ else: # all
+ q = NumericRangeQuery.newIntRange("tag_id", 0, Integer.MAX_VALUE, True, True)
+ self.index.deleteDocuments(q)
+
+ if not remove_only:
+ # then add them [all or just one passed]
+ if not tags:
+ tags = chain(catalogue.models.Tag.objects.exclude(category='set'), \
+ PDCounterAuthor.objects.all(), \
+ PDCounterBook.objects.all())
+
+ for tag in tags:
+ if isinstance(tag, PDCounterAuthor):
+ 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", 'pd_author', Field.Store.YES, Field.Index.NOT_ANALYZED))
+ doc.add(Field("is_pdcounter", 'true', Field.Store.YES, Field.Index.NOT_ANALYZED))
+ self.index.addDocument(doc)
+ elif isinstance(tag, PDCounterBook):
+ doc = Document()
+ doc.add(NumericField("tag_id", Field.Store.YES, True).setIntValue(int(tag.id)))
+ doc.add(Field("tag_name", tag.title, Field.Store.NO, Field.Index.ANALYZED))
+ doc.add(Field("tag_name_pl", tag.title, Field.Store.NO, Field.Index.ANALYZED))
+ doc.add(Field("tag_category", 'pd_book', Field.Store.YES, Field.Index.NOT_ANALYZED))
+ doc.add(Field("is_pdcounter", 'true', Field.Store.YES, Field.Index.NOT_ANALYZED))
+ self.index.addDocument(doc)
+ else:
+ 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)
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))
+ 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(book.parent.id))
+ doc.add(NumericField("parent_id", Field.Store.YES, True).setIntValue(int(book.parent.id)))
return doc
- def remove_book(self, book):
+ def remove_book(self, book_or_id, remove_snippets=True):
"""Removes a book from search index.
book - Book instance."""
- q = NumericRangeQuery.newIntRange("book_id", book.id, book.id, True, True)
+ if isinstance(book_or_id, catalogue.models.Book):
+ book_id = book_or_id.id
+ else:
+ book_id = book_or_id
+
+ q = NumericRangeQuery.newIntRange("book_id", book_id, book_id, True, True)
self.index.deleteDocuments(q)
+ if remove_snippets:
+ snippets = Snippets(book_id)
+ snippets.remove()
+
def index_book(self, book, book_info=None, overwrite=True):
"""
Indexes the book.
and calls self.index_content() to index the contents of the book.
"""
if overwrite:
- self.remove_book(book)
+ # we don't remove snippets, since they might be still needed by
+ # threads using not reopened index
+ self.remove_book(book, remove_snippets=False)
book_doc = self.create_book_doc(book)
- meta_fields = self.extract_metadata(book, book_info)
+ meta_fields = self.extract_metadata(book, book_info, dc_only=['source_name', 'authors', 'title'])
+ # let's not index it - it's only used for extracting publish date
+ if 'source_name' in meta_fields:
+ del meta_fields['source_name']
+
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']])
+ self.index_content(book, book_fields=[meta_fields['title'], meta_fields['authors'], meta_fields['published_date']])
master_tags = [
'opowiadanie',
'dramat_wierszowany_l',
'dramat_wierszowany_lp',
'dramat_wspolczesny', 'liryka_l', 'liryka_lp',
- 'wywiad'
+ 'wywiad',
+ ]
+
+ ignore_content_tags = [
+ 'uwaga', 'extra',
+ 'zastepnik_tekstu', 'sekcja_asterysk', 'separator_linia', 'zastepnik_wersu',
+ 'didaskalia',
+ 'naglowek_aktu', 'naglowek_sceny', 'naglowek_czesc',
]
- skip_header_tags = ['autor_utworu', 'nazwa_utworu', 'dzielo_nadrzedne']
+ footnote_tags = ['pa', 'pt', 'pr', 'pe']
- def extract_metadata(self, book, book_info=None):
+ 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]+)[\]. ]*$")
+
+ def extract_metadata(self, book, book_info=None, dc_only=None):
"""
Extract metadata from book and returns a map of fields keyed by fieldname
"""
# validator, name
for field in dcparser.BookInfo.FIELDS:
+ if dc_only and field.name not in dc_only:
+ continue
if hasattr(book_info, field.name):
if not getattr(book_info, field.name):
continue
fields[field.name] = Field(field.name, "%04d%02d%02d" %\
(dt.year, dt.month, dt.day), Field.Store.NO, Field.Index.NOT_ANALYZED)
+ # get published date
+ pd = None
+ if hasattr(book_info, 'source_name') and book_info.source_name:
+ match = self.published_date_re.search(book_info.source_name)
+ if match is not None:
+ pd = str(match.groups()[0])
+ if not pd: pd = ""
+ fields["published_date"] = Field("published_date", pd, Field.Store.YES, Field.Index.NOT_ANALYZED)
+
return fields
def add_gaps(self, fields, fieldname):
if master is None:
return []
- def walker(node):
- yield node, None
- for child in list(node):
- for b, e in walker(child):
- yield b, e
- yield None, node
+ def walker(node, ignore_tags=[]):
+
+ if node.tag not in ignore_tags:
+ yield node, None, None
+ if node.text is not None:
+ yield None, node.text, None
+ for child in list(node):
+ for b, t, e in walker(child):
+ yield b, t, e
+ yield None, None, node
+
+ if node.tail is not None:
+ yield None, node.tail, None
return
def fix_format(text):
+ # separator = [u" ", u"\t", u".", u";", u","]
+ if isinstance(text, list):
+ # need to join it first
+ text = filter(lambda s: s is not None, content)
+ text = u' '.join(text)
+ # for i in range(len(text)):
+ # if i > 0:
+ # if text[i][0] not in separator\
+ # and text[i - 1][-1] not in separator:
+ # text.insert(i, u" ")
+
return re.sub("(?m)/$", "", text)
def add_part(snippets, **fields):
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 snippets.revision:
+ doc.add(NumericField("snippets_revision", Field.Store.YES, True).setIntValue(snippets.revision))
if 'fragment_anchor' in fields:
doc.add(Field("fragment_anchor", fields['fragment_anchor'],
if header.tag in self.skip_header_tags:
continue
+ if header.tag is etree.Comment:
+ continue
- content = u' '.join([t for t in header.itertext()])
- content = fix_format(content)
-
- doc = add_part(snippets, header_index=position, header_type=header.tag, content=content)
-
- self.index.addDocument(doc)
+ # 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))
- for start, end in walker(header):
+ 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}
- fragments[fid]['content'].append(start.tail)
+
+ # 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(',')))
- fragments[fid]['content'].append(start.tail)
+ 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 # empty themes list.
del fragments[fid]
- def jstr(l):
- return u' '.join(map(
- lambda x: x == None and u'(none)' or unicode(x),
- l))
-
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=u' '.join(filter(lambda s: s is not None, frag['content'])),
+ content=fix_format(frag['content']),
themes=frag['themes'])
-
+ #print '@ FRAG %s' % frag['content']
self.index.addDocument(doc)
- elif start is not None:
- for frag in fragments.values():
- frag['content'].append(start.text)
- elif end is not None:
- for frag in fragments.values():
- frag['content'].append(end.tail)
+
+ # 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()
try:
f(*a)
except Exception, e:
- print("Error in indexing thread: %s" % e)
+ log.error("Error in indexing thread: %s" % e)
traceback.print_exc()
raise e
return _wrap
"""
index = None
- def open(self, analyzer=None, threads=4):
- if ReusableIndex.index is not None:
+ def open(self, analyzer=None, **kw):
+ if ReusableIndex.index:
self.index = ReusableIndex.index
else:
- print("opening index")
- Index.open(self, analyzer)
+ Index.open(self, analyzer, **kw)
ReusableIndex.index = self.index
atexit.register(ReusableIndex.close_reusable)
@staticmethod
def close_reusable():
- if ReusableIndex.index is not None:
+ if ReusableIndex.index:
ReusableIndex.index.optimize()
ReusableIndex.index.close()
ReusableIndex.index = None
+ index_changed.send_robust(None)
+
def close(self):
- pass
+ if ReusableIndex.index:
+ ReusableIndex.index.commit()
class JoinSearch(object):
class SearchResult(object):
- def __init__(self, searcher, scoreDocs, score=None, how_found=None, snippets=None):
+ 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
+ self._score = score
else:
- self.score = scoreDocs.score
+ self._score = scoreDocs.score
+
+ self.boost = 1.0
self._hits = []
- self.hits = None # processed hits
+ self._processed_hits = None # processed hits
- stored = searcher.doc(scoreDocs.doc)
+ stored = search.searcher.doc(scoreDocs.doc)
self.book_id = int(stored.get("book_id"))
+ pd = stored.get("published_date")
+ try:
+ self.published_date = int(pd)
+ except ValueError:
+ self.published_date = 0
+
header_type = stored.get("header_type")
- if not header_type:
- return
+ # 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
- 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")
- 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 []})
- 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._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
+ self._score = other._score
return self
def get_book(self):
+ if hasattr(self, '_book'):
+ return self._book
return catalogue.models.Book.objects.get(id=self.book_id)
book = property(get_book)
- def process_hits(self):
+ @property
+ def hits(self):
+ if self._processed_hits is not None:
+ return self._processed_hits
+
POSITION = 0
FRAGMENT = 1
POSITION_INDEX = 1
# 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)
+
+ # sections not covered by fragments
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],
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()
+ def remove_duplicates(lst, keyfn, compare):
+ els = {}
+ for e in lst:
+ eif = keyfn(e)
+ if eif in els:
+ if compare(els[eif], e) >= 1:
+ continue
+ els[eif] = e
+ return els.values()
+
+ # remove fragments with duplicated fid's and duplicated snippets
+ frags = remove_duplicates(frags, lambda f: f[FRAGMENT], lambda a, b: cmp(a[SCORE], b[SCORE]))
+ frags = remove_duplicates(frags, lambda f: f[OTHER]['snippets'] and f[OTHER]['snippets'][0] or f[FRAGMENT],
+ lambda a, b: cmp(a[SCORE], b[SCORE]))
# remove duplicate sections
sections = {}
hits = sections.values()
for f in frags:
- frag = catalogue.models.Fragment.objects.get(anchor=f[FRAGMENT])
+ try:
+ frag = catalogue.models.Fragment.objects.get(anchor=f[FRAGMENT], book__id=self.book_id)
+ 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': frag.tags.filter(category='theme')
+ '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.hits = hits
+ self._processed_hits = hits
- return self
+ return hits
def __unicode__(self):
return u'SearchResult(book_id=%d, score=%d)' % (self.book_id, self.score)
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)
+ 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):
IndexStore.__init__(self)
self.analyzer = WLAnalyzer() # PolishAnalyzer(Version.LUCENE_34)
# self.analyzer = WLAnalyzer()
- self.searcher = IndexSearcher(self.store, True)
+ reader = IndexReader.open(self.store, True)
+ self.searcher = IndexSearcher(reader)
self.parser = QueryParser(Version.LUCENE_34, default_field,
self.analyzer)
self.parent_filter = TermsFilter()
self.parent_filter.addTerm(Term("is_book", "true"))
+ index_changed.connect(self.reopen)
+
+ def close(self):
+ reader = self.searcher.getIndexReader()
+ self.searcher.close()
+ reader.close()
+ super(Search, self).close()
+ index_changed.disconnect(self.reopen)
+
+ def reopen(self, **unused):
+ reader = self.searcher.getIndexReader()
+ rdr = reader.reopen()
+ if not rdr.equals(reader):
+ log.debug('Reopening index')
+ oldsearch = self.searcher
+ self.searcher = IndexSearcher(rdr)
+ oldsearch.close()
+ reader.close()
def query(self, query):
"""Parse query in default Lucene Syntax. (for humans)
bks.append(catalogue.models.Book.objects.get(id=doc.get("book_id")))
return (bks, tops.totalHits)
- def get_tokens(self, searched, field='content'):
+ 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):
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):
+ @staticmethod
+ def fuzziness(fuzzy):
"""Helper method to sanitize fuzziness"""
if not fuzzy:
return None
fuzzterms = []
while True:
- # print("fuzz %s" % unicode(fuzzterm.term()).encode('utf-8'))
ft = fuzzterm.term()
if ft:
fuzzterms.append(ft)
phrase.add(term)
return phrase
- def make_term_query(self, tokens, field='content', modal=BooleanClause.Occur.SHOULD, fuzzy=False):
+ @staticmethod
+ def make_term_query(tokens, field='content', modal=BooleanClause.Occur.SHOULD, fuzzy=False):
"""
Returns term queries joined by boolean query.
modal - applies to boolean query
q.add(BooleanClause(term, modal))
return q
- # def content_query(self, query):
- # return BlockJoinQuery(query, self.parent_filter,
- # BlockJoinQuery.ScoreMode.Total)
+ 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):
"""
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, how_found="search_perfect_book"))
+ books.append(SearchResult(self, found, how_found="search_perfect_book"))
return books
def search_book(self, searched, max_results=20, fuzzy=False, hint=None):
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, how_found="search_book"))
+ 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 containt a phrase perfectly matching (with a slop of 2, default for make_phrase())
+ 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]),
max_results)
for found in top.scoreDocs:
- books.append(SearchResult(self.searcher, found, snippets=self.get_snippets(found, q), how_found='search_perfect_parts'))
+ 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):
+ 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
# content only query : themes x content
q = BooleanQuery()
- tokens_pl = self.get_tokens(searched, field='content')
- tokens = self.get_tokens(searched, field='SIMPLE')
+ 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']) != []:
topDocs = self.searcher.search(q, only_in, max_results)
for found in topDocs.scoreDocs:
- books.append(SearchResult(self.searcher, found, how_found='search_everywhere_themesXcontent'))
- print "* %s theme x content: %s" % (searched, books[-1]._hits)
+ books.append(SearchResult(self, found, how_found='search_everywhere_themesXcontent', searched=searched))
# query themes/content x author/title/tags
q = BooleanQuery()
topDocs = self.searcher.search(q, only_in, max_results)
for found in topDocs.scoreDocs:
- books.append(SearchResult(self.searcher, found, how_found='search_everywhere'))
- print "* %s scatter search: %s" % (searched, books[-1]._hits)
+ books.append(SearchResult(self, found, how_found='search_everywhere', searched=searched))
return books
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
+ revision = stored.get('snippets_revision')
+ if revision: revision = int(revision)
+
# locate content.
- snippets = Snippets(stored.get('book_id')).open()
+ book_id = int(stored.get('book_id'))
+ snippets = Snippets(book_id, revision=revision)
+
try:
- text = snippets.get((int(stored.get('snippets_position')),
- int(stored.get('snippets_length'))))
- finally:
- snippets.close()
+ snippets.open()
+ except IOError, e:
+ log.error("Cannot open snippet file for book id = %d [rev=%d], %s" % (book_id, revision, e))
+ return []
- tokenStream = TokenSources.getAnyTokenStream(self.searcher.getIndexReader(), scoreDoc.doc, field, self.analyzer)
- # highlighter.getBestTextFragments(tokenStream, text, False, 10)
- snip = highlighter.getBestFragments(tokenStream, text, 3, "...")
+ try:
+ 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, "...")
+ except Exception, e:
+ e2 = e
+ if hasattr(e, 'getJavaException'):
+ e2 = unicode(e.getJavaException())
+ raise Exception("Problem fetching snippets for book %d, @%d len=%d" % (book_id, int(position), int(length)),
+ e2)
return snip
@staticmethod
if terms:
return JArray('object')(terms, Term)
- def search_tags(self, query, filter=None, max_results=40):
+ def search_tags(self, query, filt=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([filt, self.term_filter(Term('is_pdcounter', 'true'), inverse=True)])
+ tops = self.searcher.search(query, filt, 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')
+ category = doc.get('tag_category')
+ try:
+ if is_pdcounter == 'true':
+ if category == 'pd_author':
+ tag = PDCounterAuthor.objects.get(id=doc.get('tag_id'))
+ elif category == 'pd_book':
+ tag = PDCounterBook.objects.get(id=doc.get('tag_id'))
+ tag.category = 'pd_book' # make it look more lik a tag.
+ else:
+ print "Warning. cannot get pdcounter tag_id=%d from db; cat=%s" % (int(doc.get('tag_id')), category)
+ 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)
+ except catalogue.models.Tag.DoesNotExist: pass
+ except PDCounterAuthor.DoesNotExist: pass
+ except PDCounterBook.DoesNotExist: pass
+
+ log.debug('search_tags: %s' % tags)
return tags
- def search_books(self, query, filter=None, max_results=10):
+ def search_books(self, query, filt=None, max_results=10):
"""
Searches for Book objects using query
"""
bks = []
- tops = self.searcher.search(query, filter, max_results)
+ tops = self.searcher.search(query, filt, 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")))
+ try:
+ bks.append(catalogue.models.Book.objects.get(id=doc.get("book_id")))
+ except catalogue.models.Book.DoesNotExist: pass
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, fuzzy=False):
"""
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, fuzzy=fuzzy)
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, fuzzy=False):
"""
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', fuzzy=fuzzy)
return self.search_books(q, self.term_filter(Term("is_book", "true")), max_results=max_results)
Chains a filter list together
"""
filters = filter(lambda x: x is not None, filters)
- if not filters:
+ if not filters or filters is []:
return None
chf = ChainedFilter(JArray('object')(filters, Filter), op)
return chf
fnp / wolnelektury.git / blobdiff