import errno
from librarian import dcparser
from librarian.parser import WLDocument
+from lxml import etree
import catalogue.models
from multiprocessing.pool import ThreadPool
from threading import current_thread
self.file.write(txt)
pos = (self.position, l)
self.position += l
- print "SSSS %s - %s" % (pos, txt)
return pos
def get(self, pos):
for tag in catalogue.models.Tag.objects.all():
doc = Document()
- doc.add(NumericField("tag_id", Field.Store.YES, True).setIntValue(tag.id))
+ 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))
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):
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',
+ ]
+
+ footnote_tags = ['pa', 'pt', 'pr', 'pe']
+
skip_header_tags = ['autor_utworu', 'nazwa_utworu', 'dzielo_nadrzedne']
+ published_date_re = re.compile("([0-9]+)[\]. ]*$")
+
def extract_metadata(self, book, book_info=None):
"""
Extract metadata from book and returns a map of fields keyed by fieldname
fields[field.name] = Field(field.name, "%04d%02d%02d" %\
(dt.year, dt.month, dt.day), Field.Store.NO, Field.Index.NOT_ANALYZED)
+ # get published date
+ source = book_info.source_name
+ match = self.published_date_re.search(source)
+ print("published date is %s %s" % (match, match is not None and match.groups()))
+ if match is not None:
+ fields["published_date"] = Field("published_date", str(match.groups()[0]), Field.Store.YES, Field.Index.NOT_ANALYZED)
+
return fields
def add_gaps(self, fields, fieldname):
if master is None:
return []
- def walker(node):
+ def walker(node, ignore_tags=[]):
yield node, None
- for child in list(node):
+ for child in filter(lambda n: n.tag not in ignore_tags, list(node)):
for b, e in walker(child):
yield b, e
yield None, node
return
def fix_format(text):
+ # separator = [u" ", u"\t", u".", u";", u","]
+ if isinstance(text, list):
+ # need to join it first
+ text = filter(lambda s: s is not None, content)
+ text = u' '.join(text)
+ # for i in range(len(text)):
+ # if i > 0:
+ # if text[i][0] not in separator\
+ # and text[i - 1][-1] not in separator:
+ # text.insert(i, u" ")
+
return re.sub("(?m)/$", "", text)
def add_part(snippets, **fields):
fragments = {}
snippets = Snippets(book.id).open('w')
+ position = 0
try:
- for header, position in zip(list(master), range(len(master))):
+ for header in list(master):
if header.tag in self.skip_header_tags:
continue
+ if header.tag is etree.Comment:
+ continue
# section content
content = []
+ footnote = None
+
+ for start, 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 = ' '.join(start.itertext())
+ elif end is not None and footnote is not None and end.tag in self.footnote_tags:
+ doc = add_part(snippets, header_index=position, header_type=header.tag,
+ content=footnote)
+
+ self.index.addDocument(doc)
- for start, end in walker(header):
- # handle fragments and themes.
+ footnote = None
+
+ # 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}
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'])
self.index.addDocument(doc)
# in the end, add a section text.
doc = add_part(snippets, header_index=position, header_type=header.tag,
- content=fix_format(u' '.join(filter(lambda s: s is not None, frag['content']))))
+ content=fix_format(content))
self.index.addDocument(doc)
+ position += 1
finally:
snippets.close()
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"))
header_type = stored.get("header_type")
fragment = stored.get("fragment_anchor")
+ pd = stored.get("published_date")
+ if pd is None:
+ print "published_date is none for book %d" % self.book_id
+ pd = 0
+ self.published_date = int(pd)
+
if snippets:
snippets = snippets.replace("/\n", "\n")
hit = (sec + (header_span,), fragment, scoreDocs.score, {'how_found': how_found, 'snippets': snippets and [snippets] or []})
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))
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
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])
+ 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')
+ print "THEME HIT: %s in %s" % (tokens, name_tokens)
+ 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)
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):
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):
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):
+ 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)
+ 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):
+ 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=self.get_snippets(found, query)) 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'))
+ 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
topDocs = self.searcher.search(q, only_in, max_results)
for found in topDocs.scoreDocs:
- books.append(SearchResult(self.searcher, found, how_found='search_everywhere'))
+ books.append(SearchResult(self, found, how_found='search_everywhere', searched=searched))
print "* %s scatter search: %s" % (searched, books[-1]._hits)
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
# locate content.
snippets = Snippets(stored.get('book_id')).open()
try:
- text = snippets.get((int(stored.get('snippets_position')),
- int(stored.get('snippets_length'))))
+ text = snippets.get((int(position),
+ int(length)))
finally:
snippets.close()
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