def save(self, manually_splitting=False, source_sentences=()):
if not manually_splitting:
# Tokenize the HTML that is fetched from a wiki article
sentences = list()
segment_id = 0
soup = BeautifulSoup(self.source_text)
sentence_splitter = determine_splitter(self.language)
# initial save for foreign key based saves to work
# save should occur after sent_detector is loaded
super(SourceArticle, self).save()
# find all paragraphs
for p in soup.findAll('p'):
only_p = p.findAll(text=True)
p_text = ''.join(only_p)
# split all sentences in the paragraph
sentences = sentence_splitter(p_text.strip())
# TODO: remove bad sentences that were missed above
sentences = [s for s in sentences if not re.match("^\**\[\d+\]\**$", s)]
for sentence in sentences:
# Clean up bad spaces ( )
sentence = sentence.replace(" ", " ")
s = SourceSentence(article=self, text=sentence, segment_id=segment_id)
segment_id += 1
s.save()
s.end_of_paragraph = True
s.save()
self.sentences_processed = True
else:
for sentence in source_sentences:
sentence.save()
super(SourceArticle, self).save()
def save(self, manually_splitting=False):
if manually_splitting:
print 'woo'
else:
sentences = list()
segment_id = 0
soup = BeautifulSoup(self.source_text)
sentence_splitter = determine_splitter(self.language)
# initial save for foriegn key based saves to work
# save should occur after sent_detector is loaded
super(SourceArticle, self).save()
for p in soup.findAll('p'):
only_p = p.findAll(text=True)
p_text = ''.join(only_p)
for sentence in sentence_splitter(p_text.strip()):
s = SourceSentence(article=self,
text=sentence,
segment_id=segment_id)
segment_id += 1
s.save()
s.end_of_paragraph = True
s.save()
self.sentences_processed = True
print 'James :: %s' % self
super(SourceArticle, self).save()
def save(self):
sentences = list()
segment_id = 0
#soup = BeautifulSoup(self.source_text)
sentence_splitter = determine_splitter(self.language)
# initial save for foriegn key based saves to work
# save should occur after sent_detector is loaded
super(SourceArticle, self).save()
#for p in soup.findAll('p'):
# only_p = p.findAll(text=True)
# p_text = ''.join(only_p)
# for sentence in sentence_splitter(p_text.strip()):
# s = SourceSentence(article=self, text=sentence, segment_id=segment_id)
# segment_id += 1
# s.save()
# s.end_of_paragraph = True
import sys
print >> sys.stderr, 'got here...'
for sent,tag in zip(*wiki2sentences(self.source_text,sentence_splitter)):
s = SourceSentence(article=self, text=sent, segment_id=segment_id)
segment_id += 1
if tag=='LastSentence':
s.end_of_paragraph = True
s.save()
self.sentences_processed = True
super(SourceArticle, self).save()
def save(self, manually_splitting=False, source_sentences=()):
if not self.sentences_processed and not manually_splitting:
soup = BeautifulSoup(self.source_text)
sentence_splitter = determine_splitter(self.language.code)
super(SourceArticle, self).save()
segment_id = 0
for tag in soup.findAll(re.compile('^[ph]')):
if re.match('p', tag.name):
p_text = ''.join([x.string for x in tag.findAll(text=True)
if not re.match('[\[\]\\d]+$',
x.string)])
sentences = sentence_splitter(p_text.strip())
for sentence in sentences:
sentence = sentence.replace(" ", " ")
src_sent = SourceSentence(article=self,
text=sentence,
segment_id=segment_id,
is_heading=False,
heading_level=0)
segment_id += 1
src_sent.save()
src_sent.end_of_paragraph = True
src_sent.save()
elif re.match('h\d', tag.name):
headline = tag.findAll(attrs={'class': 'mw-headline'})
if headline:
content = headline[0].string
else:
content = tag.string
if content.lower() == 'weblinks':
break
src_sent = SourceSentence(article=self,
text=content,
segment_id=segment_id,
is_heading=True,
heading_level=int(tag.name[-1]))
src_sent.save()
segment_id += 1
self.sentences_processed = True
else:
for sentence in source_sentences:
sentence.save()
super(SourceArticle, self).save()
def save(self):
sentences = list()
segment_id = 0
soup = BeautifulSoup(self.source_text)
sentence_splitter = determine_splitter(self.language)
# initial save for foriegn key based saves to work
# save should occur after sent_detector is loaded
super(SourceArticle, self).save()
for p in soup.findAll('p'):
only_p = p.findAll(text=True)
p_text = ''.join(only_p)
for sentence in sentence_splitter(p_text.strip()):
s = SourceSentence(article=self, text=sentence, segment_id=segment_id)
segment_id += 1
s.save()
s.end_of_paragraph = True
s.save()
self.sentences_processed = True
super(SourceArticle, self).save()
def save(self, manually_splitting=False, source_sentences=()):
if not self.sentences_processed and not manually_splitting:
# Tokenize the HTML that is fetched from a wiki article
sentences = list()
segment_id = 0
soup = BeautifulSoup(self.source_text)
sentence_splitter = determine_splitter(self.language.code)
# initial save for foreign key based saves to work
# save should occur after sent_detector is loaded
super(SourceArticle, self).save()
# find all paragraphs
for p in soup.findAll('p'):
only_p = p.findAll(text=True)
p_text = ''.join(only_p)
# split all sentences in the paragraph
sentences = sentence_splitter(p_text.strip())
# TODO: remove bad sentences that were missed above
sentences = [
s for s in sentences if not re.match("^\**\[\d+\]\**$", s)
]
for sentence in sentences:
# Clean up bad spaces ( )
sentence = sentence.replace(" ", " ")
s = SourceSentence(article=self,
text=sentence,
segment_id=segment_id)
segment_id += 1
s.save()
s.end_of_paragraph = True
s.save()
self.sentences_processed = True
else:
for sentence in source_sentences:
sentence.save()
super(SourceArticle, self).save()
def write_lines_to_file(output_filename, lines):
""" \
Writes a list of lines to file. \
"""
output_file = open(output_filename, 'w')
for line in lines:
output_file.write(line.encode('UTF-8'))
output_file.write('\n'.encode('UTF-8'))
output_file.close()
return lines
#topics = read_lines_from_file('/Users/bahn/work/wikitopics/data/clustering/pick/pick0127')
date = datetime.date(2009, 10, 12)
lang = 'en'
sentences,tags = wpTextExtractor.wiki2sentences("<!-- See -->\n<!-- PLEASE DO NOT CHANGE OBAMA'S NAME -->", determine_splitter(lang), True)
for s in sentences:
print s
sys.exit(0)
#topics = ['Inauguration_of_Barack_Obama', 'Bill_Clinton', 'Black_Saturday_bushfires', 'Estradiol','Emma_Frost','Influenza','James','Brett_Favre']
topics = ['Barack_Obama']
shown = {}
shown2 = {}
shown3 = {}
for article in topics:
revid = wikipydia.query_revid_by_date(article, lang, date)
print revid
wikimarkup = wikipydia.query_text_raw_by_revid(revid, lang)['text']
sentences,tags = wpTextExtractor.wiki2sentences(wikimarkup, determine_splitter(lang), True)
wikimarkup = '\n'.join(sentences)
