def new_microblog():
form = MicroblogForm()
if form.validate_on_submit():
microblog = Microblog(body=form.microblog.data,author=current_user)
db.session.add(microblog)
db.session.commit()
flash('Your microblog is now live!')
return redirect(url_for('main.new_microblog'))
page = request.args.get('page',1,type=int)
pagination = current_user.followed_microblogs().paginate(
page,current_app.config['POSTS_PER_PAGE'])
microblogs = pagination.items
return render_template('microblog/new_microblog.html',form=form, microblogs=microblogs, pagination=pagination)
def test_feature():
microblogId, microblog_text, polarity = "234", "我不喜欢你， 你这个愚昧的家伙，脑子有毛病", 1
feature_extracter = FeatureExtractor()
words, taggings = feature_extracter.pos_tagging(microblog_text)
posCount, negCount = feature_extracter.polarity_count(microblog_text)
single_microblog = Microblog(microblogId=microblogId,
text=microblog_text,
polarity=polarity,
negCount=negCount,
posCount=posCount,
words=words,
taggings=taggings,
microblogType=1,
topic=None,
sentiment=None)
single_microblog.save()
def complete_microblog():
microblogs = Microblog.objects(polarity='pos', microblogType='training')
print(len(microblogs))
new_microblogs = []
for microblog in microblogs:
newone = Microblog(microblogId=microblog.microblogId,
text=microblog.text,
polarity=microblog.polarity,
negCount=microblog.negCount,
posCount=microblog.posCount,
words=microblog.words,
taggings=microblog.taggings,
microblogType=microblog.microblogType,
topic='',
sentiment='')
new_microblogs.append(newone)
Microblog.objects.insert(new_microblogs)
def microblog_data_handler(microblog_type):
data_filter = DataFilter()
microblogs = data_filter.read_and_filter_api_microblog_data(microblog_type)
result = []
feature_extractor = FeatureExtractor()
for polarity in microblogs:
microblog_list = microblogs[polarity]
for microblog in microblog_list:
#feature extractor
microblogId, microblog_raw_text, microblog_text, polarity = microblog[
0], microblog[1], microblog[2], microblog[3]
posCount, negCount = feature_extractor.polarity_count(
microblog_text)
words, taggings = feature_extractor.pos_tagging(microblog_text)
raw_words, raw_taggings = feature_extractor.pos_tagging(
microblog_raw_text)
single_microblog = Microblog(microblogId=microblogId,
text=microblog_text,
polarity=polarity,
microblogType=microblog_type,
topic='',
posCount=posCount,
negCount=negCount,
words=words,
taggings=taggings,
raw_words=raw_words,
raw_taggings=raw_taggings,
sentiment='')
result.append(single_microblog)
return result