def get_code(email, upload_at):
user_id = select_user_id(email)
if user_id == '':
data = {'email': '0', 'code': '0'}
final = json.dumps(data, ensure_ascii=False).encode('utf8')
return final
else:
code = select_code(user_id)
if code == '':
code = utils.create_code()
query = "INSERT INTO code_user (user_id, code, upload_at) VALUES (%s,%s,%s);"
data = (user_id, code, upload_at)
conn.run_query(query, data)
data = {'email': email, 'code': utils.remove_punctuation(str(code))}
final = json.dumps(data, ensure_ascii=False).encode('utf8')
mservice.send_email("*****@*****.**",
"Rodolfo123123",
email,
"Tu código es: "+str(code))
return final
else:
data = {'email': email, 'code': utils.remove_punctuation(str(code))}
final = json.dumps(data, ensure_ascii=False).encode('utf8')
mservice.send_email("*****@*****.**",
"Rodolfo123123",
email,
"Tu código es: " + str(code))
return final
def search(paragraph):
paragraph = split(lower(remove_punctuation(paragraph)))
for i in topic:
for j in paragraph:
if i == j:
return True
return False
def start(paragraphs):
for word in topic:
s = split(remove_punctuation(lower(paragraphs)))
for i in s:
if i == word:
return True
return False
def about_helper(paragraph):
paragraph = remove_punctuation(lower(paragraph)).split()
# print(paragraph)
for i in topic:
if i in paragraph:
return True
return False
def select(paragraph):
remove_punctuation_paragraph = remove_punctuation(paragraph) # remove punction
split_paragraph_list = split(remove_punctuation_paragraph) #split paragraph
for splited_paragraph in split_paragraph_list:
if lower(splited_paragraph) in topic: # return a lowercased version
return True
return False
def is_about_topic(s):
low_s = lower(remove_punctuation(s))
for _s in split(low_s):
for _topic in topic:
if _s == _topic:
return True
return False
def helper(str):
str = split(remove_punctuation(lower(str)))
for i in range(0, len(str)):
for j in range(0, len(topic)):
if (str[i] == topic[j]):
return True
return False
def f(x):
splitted = split(x)
ls = [lower(remove_punctuation(s)) for s in splitted]
for item in ls:
if item in topic:
return True
return False
def sentence_about(sentence):
words = split(sentence)
words = [lower(remove_punctuation(w)) for w in words]
for w in words:
if w in topic:
return True
return False
def helpler(paragraph):
new_para = split(lower(remove_punctuation(paragraph)))
for i in new_para:
for x in topic:
if i == x:
return True
return False
def select(paragraphs):
paragraphs = lower(paragraphs)
paragraphs = remove_punctuation(paragraphs)
list_paragraphs = split(paragraphs)
for words in topic:
if words in list_paragraphs:
return True
return False
def update_password(email, code, password):
user_id = select_user_id(email)
code_consult = select_code(user_id)
code_consult = utils.remove_punctuation(str(code_consult))
if code_consult == code:
query = "UPDATE user SET password = %s WHERE user_id = %s;"
data = (password, user_id)
conn.run_query(query, data)
def calculate_word_vector_model(input_path, output_path=None):
document = []
for line in open(input_path):
line = utils.remove_punctuation(line)
cutted_line = jieba.cut(line)
document.append(list(cutted_line))
model = gensim.models.Word2Vec(document)
model.save(output_path)
return model
def calculate_word_vector_model(input_path,output_path = None):
document = []
for line in open(input_path):
line = utils.remove_punctuation(line)
cutted_line = jieba.cut(line)
document.append(list(cutted_line))
model = gensim.models.Word2Vec(document)
model.save(output_path)
return model
def f(p):
p = remove_punctuation(p)
p = lower(p)
p = split(p)
for i in p:
for j in topic:
if i == j:
return True
return False
def func(paragraph):
paragraph = split(remove_punctuation(lower(paragraph)))
filtered = [x for x in topic if x in paragraph]
if filtered != []:
return True
else:
return False
def is_topic_mentioned(
paragraph): #parapraph is a string,choose from def choose
lowered_paragraph = lower(paragraph)
lowered_nopunc_paragraph = remove_punctuation(lowered_paragraph)
lowered_nopunc_paragraph_list = split(lowered_nopunc_paragraph)
for keyword in topic:
if keyword in lowered_nopunc_paragraph_list:
return True
return False
def valid_topic(paragraph):
paragraph = remove_punctuation(paragraph)
paragraph = lower(paragraph)
split_paragraph = split(paragraph)
for split_words in split_paragraph:
if split_words in topic:
return True
return False
def select(paragraph):
paragraph = remove_punctuation(paragraph)
paragraph = lower(paragraph)
# list of all words in paragraph
paragraph = split(paragraph)
for word in topic:
if (word in paragraph):
return True
return False
def make_id_for_entry(entry, style='gscholar'):
"""Take entry as a dict, and return an ID to use for the bib entry."""
if style != 'gscholar':
raise NotImplementedError('Not implemented yet.')
try:
entry['title']
except KeyError:
logger.info('Title entry missing. Could not create id for entry.')
logger.info(entry)
raise KeyError('I could not find title information from the given DOI/'
'arXiv. This often happens with books, which for some r'
'easons often do no include the title information.')
try:
entry['author']
entry['year']
except KeyError:
# try to pull down additional information from google scholar
logger.info('I could not find author/year information from DOI/arxiv,'
' attempting to pull information down from gscholar.')
gscholar_result = pull_info_from_gscholar(
entry['title'], accepted_fields=['author', 'year'])
if 'author' in gscholar_result and 'year' in gscholar_result:
logger.info('Author/year information pulled from scholar.')
entry.update(gscholar_result)
else:
raise KeyError("author, title and year are required.")
title = entry['title']
logger.info('I found the title "{}"'.format(title))
year = entry['year']
author = entry['author'].split(',')[0].lower()
# extract first author
if author[0] == '{':
author = author[1:]
if author[-1] == '}':
author = author[:-1]
if ' ' in author:
author = author.split(' ')[0]
# -- extract first word (looking at "words" with more than 3 chars) --
# gather all words in the title
words_in_title = re.findall(r'\S+', title)
# remove punctuation from words
words_in_title = [utils.remove_punctuation(w) for w in words_in_title]
# filter words with less than 3 chars
words_in_title = [w for w in words_in_title if len(w) > 3]
# extract first word
first_word = words_in_title[0].lower()
if first_word[0] == '{':
first_word = first_word[1:]
if first_word[-1] == '}':
first_word = first_word[:-1]
if '-' in first_word:
first_word = first_word.split('-')[0]
# build new id
newid = '{}{}{}'.format(author, year, first_word)
logger.info('New id for the given entry: `{}`'.format(newid))
return newid
def tag_comments_test(self, comments):
comments = utils.remove_punctuation(comments)
phrase_tag = set()
phrase_list = comments.split(' ')
for p in phrase_list:
for t in self.tags_repo:
match_part, if_same = wordvec.compare_phrase(p.strip(), t.strip(),self.model)
if if_same:
phrase_tag.add((p.strip(),t.strip()))
return phrase_tag
def select(string):
# need to make lowercase and remove punctuation
s = remove_punctuation(string)
s = lower(s)
# split for comparing
s = split(s)
for i in topic:
if i in s:
return True
return False
def updatePassword(email, code, password):
em = selectUserID(email)
code_old = selectCode(em)
code_old = utils.remove_punctuation(str(code_old))
if (code_old == code):
query = "UPDATE user SET password = %s WHERE user_id = %s"
data = (password, em)
conn.run_query(query, data)
def tag_comments_test(self, comments):
comments = utils.remove_punctuation(comments)
phrase_tag = set()
phrase_list = comments.split(' ')
for p in phrase_list:
for t in self.tags_repo:
match_part, if_same = wordvec.compare_phrase(
p.strip(), t.strip(), self.model)
if if_same:
phrase_tag.add((p.strip(), t.strip()))
return phrase_tag
def tag_comments_database(self, comments):
comments = utils.remove_punctuation(comments)
print comments
phrase_tag = set()
phrase_list = comments.split(' ')
for p in phrase_list:
for t in self.tags_repo:
match_part, if_same = wordvec.compare_phrase(p, t, self.model)
if if_same:
phrase_tag.add(t)
return phrase_tag
def __iter__(self):
with open(ANT_NLP_FILE_PATH, "r", encoding="utf8") as atec:
logging.info('generating word corpus, processing file %s',
ANT_NLP_FILE_PATH)
for line in atec:
line_code, s1, s2, label = line.strip().split("\t")
s1 = utils.remove_punctuation(s1)
s2 = utils.remove_punctuation(s2)
yield list(jieba.cut(s1)) + list(jieba.cut(s2))
for file in extract_wiki.list_all_files(PROCESSED_WIKI_FILE_PATH):
logging.info('generating word corpus, processing file %s', file)
with open(file, 'r', encoding="utf8") as wiki:
for line in wiki:
line = utils.remove_punctuation(line)
if len(line) > 0:
# 汉字的unicode编码范围是[0x4E00,0x9FA5]
yield [
word for word in list(jieba.cut(line))
if word and 0x4E00 <= ord(word[0]) <= 0x9FA5
]
def tag_comments_database(self, comments):
comments = utils.remove_punctuation(comments)
print comments
phrase_tag = set()
phrase_list = comments.split(' ')
for p in phrase_list:
for t in self.tags_repo:
match_part, if_same = wordvec.compare_phrase(p, t,self.model)
if if_same:
phrase_tag.add(t)
return phrase_tag
def __iter__(self):
with open(ANT_NLP_FILE_PATH, "r", encoding="utf8") as atec:
logging.info('generating char corpus, processing file %s',
ANT_NLP_FILE_PATH)
for line in atec:
lineno, s1, s2, label = line.strip().split("\t")
s1 = utils.remove_punctuation(s1)
s2 = utils.remove_punctuation(s2)
yield list(s1) + list(s2)
for file in extract_wiki.list_all_files(PROCESSED_WIKI_FILE_PATH):
logging.info('generating char corpus, processing file %s', file)
with open(file, 'r', encoding="utf8") as wiki:
for line in wiki:
line = utils.remove_punctuation(line)
if len(line) > 0:
yield [
char for char in line
if char and 0x4E00 <= ord(char[0]) <= 0x9FA5
]
def train_word_vector(source,dict,wordvec):
utils.jieba_add_dict(dict)
comments_df = DataFrame.from_csv(source,sep = '\t')
document = []
for line in comments_df['comment'].values:
line = utils.remove_punctuation(line)
cutted_line = jieba.cut(line)
document.append(list(cutted_line))
model = gensim.models.Word2Vec(document)
print 'saving word vector model'
model.save(wordvec)
return model
def train_word_vector(source, dict, wordvec):
utils.jieba_add_dict(dict)
comments_df = DataFrame.from_csv(source, sep='\t')
document = []
for line in comments_df['comment'].values:
line = utils.remove_punctuation(line)
cutted_line = jieba.cut(line)
document.append(list(cutted_line))
model = gensim.models.Word2Vec(document)
print 'saving word vector model'
model.save(wordvec)
return model
def clean(text): text = remove_accents(text) text = expand_contractions(text) text = handle_units(text) text = convert_word_to_number(text) text = remove_punctuation(text) doc = nlp(text) text = perform_spell_check(doc) doc = nlp(text) text = convert_plural_to_singular(doc) return text
def insertCode(email, upload_at):
user_id = selectUserID(email)
if user_id == '':
data = {'email': '0', 'code': '0'}
final = final = json.dumps(data, ensure_ascii=False).encode('utf8')
return final
else:
em = selectUserID(email)
code = selectCode(em)
if code == '':
code = utils.createCode()
query = "INSERT INTO code_user (user_id, code, upload_at) VALUES (%s,%s,%s) ;"
data = (em, code, upload_at)
conn.run_query(query, data)
data = {'email': email, 'code': code}
final = final = json.dumps(data, ensure_ascii=False).encode('utf8')
mservice.sendEmail(
"*****@*****.**", "Qchw-2017", email,
str(code) + " is your Quechua ASR verification code")
return final
else:
code_old = selectCode(em)
data = {
'email': email,
'code': utils.remove_punctuation(str(code_old))
}
final = final = json.dumps(data, ensure_ascii=False).encode('utf8')
mservice.sendEmail(
"*****@*****.**", "Qchw-2017", email,
utils.remove_punctuation(str(code_old)) +
" is your Quechua ASR verification code")
return final
def main(args):
"""
This processes the output of fairseq-generate so that it can be scored with sacrebleu and
so that it has the shared task format.
"""
cands = []
seen_cands = set()
current_source = None
for line in args.infile:
tokens = line.strip().split("\t")
if line.startswith("S-"):
# it's hard to have fairseq pass prompt ids through the training/evaluation process
# so we resort to regenerating ids based on the prompt text.
# we have to be careful that the text is *exactly* the same, or the id generation will be wrong.
current_source = debpe.clean(
tokens[1]) if not args.no_clean else tokens[1]
textID = makeID(current_source)
print(f"\n{textID}{FIELDSEP}{current_source}", file=args.outfile)
cands = []
seen_cands.clear()
elif line.startswith("T-"):
pass
elif line.startswith("H-") and len(tokens) == 3 and not '-inf' in line:
score = float(tokens[1])
if len(cands) == 0:
top_score = score
if args.threshold != 0.0:
prompt_threshold = (-1.0 * args.threshold) + top_score
# this is the prediction, there may be many of these.
if ((args.candlimit == -1 or len(cands) < args.candlimit) and \
(args.threshold == 0.0 or score > prompt_threshold)):
hyp = debpe.clean(
tokens[2]) if not args.no_clean else tokens[2]
hyp = hyp.lower()
# remove language code if present
if hyp.startswith("<") and len(hyp) >= 4 and hyp[3] == '>':
hyp = hyp[5:]
if args.remove_punctuation:
hyp = remove_punctuation(hyp)
if not hyp in seen_cands:
print(hyp, file=args.outfile)
cands.append(hyp)
seen_cands.add(hyp)
def tag_comments(comment, keys):
tags = set()
comment = utils.remove_punctuation(comment)
comment = comment.strip(' ')
split_comment = comment.split(' ')
ff = open('../data/tag_comments', 'w')
for phrase in split_comment:
phrase = phrase.strip(' ')
for key in keys:
if phrase.find(key) > -1:
if len(phrase) < 7 and len(phrase) > 2:
#len(phrase) 返回的是中文字的个数，不是真实长度（中文字×3）
comment = comment.replace(phrase, "$%s$" % (phrase))
tags.add(phrase)
result = "%s >> %s" % (comment.rstrip(), "\t".join(list(tags)))
return result
def tag_comments(comment, keys):
tags = set()
comment = utils.remove_punctuation(comment)
comment = comment.strip(" ")
split_comment = comment.split(" ")
ff = open("../data/tag_comments", "w")
for phrase in split_comment:
phrase = phrase.strip(" ")
for key in keys:
if phrase.find(key) > -1:
if len(phrase) < 7 and len(phrase) > 2:
# len(phrase) 返回的是中文字的个数，不是真实长度（中文字×3）
comment = comment.replace(phrase, "$%s$" % (phrase))
tags.add(phrase)
result = "%s >> %s" % (comment.rstrip(), "\t".join(list(tags)))
return result
def test_remove_punctuation(self):
tester = "-,.:"
tester = utils.remove_punctuation(tester)
self.assertTrue(tester == " ")