def word_translator(words):
b = TextBlob(words)
if b.detect_language() == "en":
print "The word " + words + " is in english and means",\
b.translate(to="es")
elif b.detect_language() == "es":
print "La palabra " + words +\
" esta en espanol y en ingles significa", b.translate(to="en")
return
def word_translator(words):
b = TextBlob(words)
if b.detect_language() == "en":
print "The word " + words + " is in english and means",\
b.translate(to="es")
elif b.detect_language() == "es":
print "La palabra " + words +\
" esta en espanol y en ingles significa", b.translate(to="en")
return
def flat_doc(document, model, extremes=None):
flat_doc = ""
for field in document:
if not isinstance(document[field], list): continue #No tomamos en cuenta los campos 'id' y '_version_': auto-generados por Solr
for value in document[field]:
## Detección y traducción ##
if field=='author.authors.authorName' or field=='author.authorBio' or field=='description' or field=='quotes.quoteText':
value_blob = TextBlob(value)
try:
if value_blob.detect_language() != 'en':
try:
value = value_blob.translate(to='en')
except Exception as e:
value = value #e = NotTranslated('Translation API returned the input string unchanged.',)
except Exception as e:
value = value #e = TranslatorError('Must provide a string with at least 3 characters.')
############################
flat_doc += str(value)+' ' #Se aplana el documento en un solo string
flat_doc = preprocess_string(flat_doc, CUSTOM_FILTERS) #Preprocesa el string
flat_doc = [w for w in flat_doc if w not in stop_words] #Remueve stop words
if extremes:
flat_doc = [w for w in flat_doc if w not in extremes]
flat_doc = [w for w in flat_doc if w in model.vocab] #Deja sólo palabras del vocabulario
if flat_doc == []:
flat_doc = ['book'] #Si el libro queda vacío, agregarle un token para no tener problemas más adelante
return flat_doc
def get_translate(self, text):
text = text.replace("text:", "")
blob = TextBlob(text)
lan = blob.detect_language()
if lan != 'en':
sentp = blob.translate(to="en")
else:
sentp = blob.translate(to="fa")
sent = self.sender.sendMessage(str(sentp))
self._editor = telepot.helper.Editor(self.bot, sent)
self._edit_msg_ident = telepot.message_identifier(sent)
def handle_message_event(event):
print(event)
text = event.message.text
source = event.source
id = ''
if isinstance(source, SourceUser):
id = source.user_id
elif isinstance(source, SourceGroup):
id = source.group_id
set_send_id(id)
blob = TextBlob(text)
if '狀態' in text:
text = text.replace('狀態', '')
if text == '':
line_bot_api.reply_message(
event.reply_token, TextSendMessage(text=get_all_messages()))
else:
name = text
line_bot_api.reply_message(event.reply_token,
TextSendMessage(text=get_message(name)))
elif '報告' in text:
matches = re.search('(.*)報告(\d*)', text)
if matches.group(1) == '' and matches.group(2) == '':
line_bot_api.reply_message(event.reply_token,
TextSendMessage(text=get_all_reports()))
elif matches.group(2) == '':
line_bot_api.reply_message(
event.reply_token,
TextSendMessage(text=get_report(matches.group(1))))
else:
line_bot_api.reply_message(
event.reply_token,
TextSendMessage(text=get_report_url(matches.group(1),
int(matches.group(2)))))
elif '敬禮' in text:
line_bot_api.reply_message(event.reply_token,
TextSendMessage(text='敬禮'))
elif '安安' in text:
line_bot_api.reply_message(event.reply_token,
TextSendMessage(text='安'))
elif '0.0' in text:
line_bot_api.reply_message(event.reply_token,
TextSendMessage(text='0.0'))
elif blob.detect_language() == 'ru':
line_bot_api.reply_message(
event.reply_token,
TextSendMessage(text=str(blob.translate(to='zh-TW'))))
def import_text(text, title=None):
"""
Import a text.
"""
blob = TextBlob(text)
document = Document()
if title is None:
first_sentence = blob.sentences[0]
if len(first_sentence) > 50:
chunk = first_sentence[0:47]
last_space = chunk.rfind(" ")
title = "{0}...".format(first_sentence[0:last_space])
document.title = title
document.text = text
document.language = blob.detect_language()
sentiment = blob.sentiment
document.polarity = sentiment[0]
document.subjectivity = sentiment[1]
document.is_tagged = False
document.save()
return document
