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parser_module.py
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457 lines (429 loc) · 19.1 KB
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from nltk.corpus import stopwords
from document import Document
import re
import math
from stemmer import PorterStemmer
class Parse:
def __init__(self):
self.stop_words = stopwords.words('english')
self.dictionary_term_index = {}
self.array_names_and_entities = {}
self.porter_stemmer = PorterStemmer()
def parse_sentence(self, text, stemmer=False):
"""
This function tokenize, remove stop words and apply lower case for every word within the text
:param text:
:return:
"""
list_percent = ["percent", "Percent", "Percentage", "percentage"]
self.array_names_and_entities = {}
self.dictionary_index = {}
text = text.replace("\n", ". ")
text = self.ignore_emojis(text)
array_text_space = text.split(" ")
array_text_space = self.separate_words_with_dots(array_text_space)
string_ans = ""
array_size = range(len(array_text_space))
string_ans_index = 0
entities_url = [] # help us to replace the url to "" because in get_entities it returns parts of the url
for word, idx in zip(array_text_space, array_size):
ans = ""
if word == '' or word == ' ': continue
check_digit = self.isdigit(word)
if len(word) < 2 and check_digit is False: continue
if len(word) < 2 or self.is_ascii(word) is False:
if check_digit is False:
word = self.remove_panctuation(word)
if self.is_ascii(word) is False or word == '' or word == " " or len(
word) < 2 or word.lower() not in self.stop_words:
continue
if ans == "" and self.is_url(word):
entities_url.append(word)
if "t.co" in word: continue
ans = self.parse_url(word)
if ans == "":
entities_url.remove(word)
continue
else:
if ans == "" and len(word) < 2 and word[0] != '#' and self.is_ascii(word) and not self.isfloat(word):
word = self.remove_panctuation(word)
if ans == "" and word[0] == '#':
temp_word = self.remove_panctuation(word)
if temp_word == "" or temp_word == "#":
continue
ans = self.parse_hashtag(temp_word)
elif ans == "" and word[0] == '@':
ans = self.remove_panctuation(word)
elif ans == "" and word in list_percent:
if idx > 0 and self.isfloat(array_text_space[idx - 1]):
ans = self.parse_percentage(array_text_space[idx - 1] + " " + word)
string_ans = string_ans[:len(string_ans) - 1 - len(ans)] + string_ans[
len(string_ans) + len(word):] + " "
else:
ans = word
elif ans == "" and (word.lstrip('-').isdigit() or self.isfloat(word.lstrip('-')) or self.isFraction(
word.lstrip('-')) or word.replace('~', '').isdigit()):
ans = self.convert_str_to_number(array_text_space, idx)
if ans == "":
pre_ans = self.remove_panctuation(word)
if len(pre_ans) < 2: continue
array_ans = pre_ans.split()
for word_array in array_ans:
if word_array.lower() in self.stop_words: continue
string_ans += self.add_to_dictionary(word_array.lower(), string_ans_index)
string_ans_index += len(word) + 1
else:
string_ans += self.add_to_dictionary(ans, string_ans_index)
string_ans_index += len(word) + 1
self.get_name_and_entities(entities_url, array_text_space)
array_parsed = string_ans.split()
return array_parsed, self.array_names_and_entities
def separate_words_with_dots(self, array_text):
new_text = ""
length = range(len(array_text))
for i in length:
word = array_text[i]
if '.' not in word:
new_text += word + " "
continue
if "http" in word or "www" in word or "t.co" in word or self.isfloat(word):
new_text += word + " "
continue
separate = str(word).split('.')
new_text += separate[0] + ". " + separate[1] + " "
return new_text.lstrip().split(" ")
def is_url(self, text):
'''
check if string is a url path
:param text: url
:return: boolean
'''
regex = re.compile(
r'^(?:http|ftp)s?://|(?:www)?.' # http:// or https://
r'(?:(?:[A-Z0-9](?:[A-Z0-9-]{0,61}[A-Z0-9])?\.)+(?:[A-Z]{2,6}\.?|[A-Z0-9-]{2,}\.?)|' # domain...
r'localhost|' # localhost...
r'\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3})' # ...or ip
r'(?::\d+)?' # optional port
r'(?:/?|[/?]\S+)$', re.IGNORECASE)
return re.match(regex, text) is not None
def add_to_dictionary(self, text, index):
array_of_words = text.split(" ")
ans = ""
for word in array_of_words:
ans += word + " "
self.dictionary_index[word] = index
if ans == "": return ""
return ans
def parse_hashtag(self, phrase):
""""
parser hash tag and lower the letters
return array of string
#stayAtHome -> ['#stayathome',stay,at,home]
"""
original_phrase = phrase
pattern = re.compile(r"[A-Z][a-z]+|\d+|[A-Z]+(?![a-z])")
if phrase[1].islower() and '_' not in original_phrase:
phrase = phrase[:1] + phrase[1].upper() + phrase[2:]
temp = pattern.findall(phrase)
all_words = phrase[1:].split("_")
for word in all_words:
if word != phrase[1:] and word.lower() and word not in temp: temp.append(word)
temp = [str_to_lower.lower() for str_to_lower in temp]
temp.insert(0, original_phrase[0:len(original_phrase)].lower().replace('_', ''))
i=0
len_temp =len(temp)
while i < len_temp:
if temp[i] in self.stop_words or len(temp[i]) < 2:
temp[i] = ''
i += 1
# for word in temp:
# if word in self.stop_words or len(word) < 2:
# temp.remove(word)
return " ".join(temp).lstrip().rstrip()
def parse_url(self, string):
"""
parsing url path
return an array of the components
"""
if string is not None:
ans = string.split("/")
#r = re.split('[/://?=-]', string)
#ans = " ".join(r).lstrip()
#for term in ans:
# term = re.sub(r"http\S+", "", ans)
#ans = "".join(ans).strip().split()
ans_len = len(ans)
remove_www = ""
if ans_len > 0:
for term in ans:
remove_www += term.replace("www.", "") + " "
ans[0] = ans[0].replace(ans[0], remove_www)
string_without_stopword = ""
length = range(len(ans))
ans_string = ans[0].split(" ")
for word, idx in zip(ans_string, length):
if word == '' or word == ' ': continue
if len(word) < 2 or (len(word) > 0 and word[0] == '#'): continue
if word not in self.stop_words or word.isnumeric():
if not self.is_url(word):
word = self.remove_panctuation(word)
string_without_stopword += word + " "
return string_without_stopword.lstrip()
else:
return ""
def isdigit(self, word):
if "0" <= word <= "9":
return True
return False
def isfloat(self, value):
"""
check if value is a float number
:return: boolean
"""
try:
float(value)
return True
except ValueError:
return False
def isFraction(self, token):
"""
check if value is a fraction number
:return: boolean
"""
if '/' not in token:
return False
values = token.split('/')
return all(i.isdigit() for i in values)
def convert_str_to_number_kmb(self, word):
"""
check if value is a float number, and return the wanted number. etc: 1000->1K, 1013456->1.013M
:return: boolean
"""
tmb = ''
if word >= 1000000000 or word <= -1000000000:
word = float(word / 1000000000)
tmb = 'B'
elif word >= 1000000 or word <= -1000000:
word = float(word / 1000000)
tmb = 'M'
elif word >= 1000 or word <= -1000:
word = float(word / 1000)
tmb = 'K'
ans = '{:0.3f}'.format(word)
return '{0:g}'.format(float(ans)) + tmb
def convert_str_to_number(self, text_demo, idx):
"""
check every type of number and return it as a string. etc: 1K,1M,1B,-900,23/5,2020,2K
:return: boolean
"""
help_minus = ''
text_return = []
my_word = text_demo[idx]
text_demo_length = len(text_demo)
my_word = my_word.replace(",", "")
if re.search('-', my_word):
help_minus = '-'
my_word = my_word.replace("-", "")
if not self.isfloat(my_word): my_word = self.remove_panctuation(my_word)
if self.isFraction(my_word):
if idx + 1 == text_demo_length:
return ''.join(help_minus + my_word)
text_return = ''.join(help_minus + my_word)
token_next = text_demo[idx + 1].lower()
if token_next == "billion" or token_next == "billions":
text_return += 'B'
text_demo[idx + 1] = ""
if token_next == "million" or token_next == "millions":
text_return += 'M'
text_demo[idx + 1] = ""
if text_demo[idx + 1] == "thousand" or token_next == "thousands":
text_return += 'K'
text_demo[idx + 1] = ""
return help_minus + ''.join(text_return)
if my_word != '' and not math.isnan(float(my_word)):
number = float(my_word)
number_numerize = self.convert_str_to_number_kmb(number)
if idx + 1 < len(text_demo):
token_next = text_demo[idx + 1].lower()
number_to_input = str(number_numerize)
if token_next == "billion" or token_next == "billions":
if 'K' in number_numerize or 'M' in number_numerize:
number_to_input = (number_to_input.translate({ord('K'): None}))
number_to_input = (number_to_input.translate({ord('M'): None}))
text_return.append(my_word)
else:
text_return.append(str(number_numerize + 'B'))
text_demo[idx + 1] = ""
elif token_next == "million" or token_next == "millions":
if 'K' in number_numerize:
number_to_input = (number_to_input.translate({ord('K'): None}))
text_return.append(number_to_input + 'B')
else:
number_to_input = str(number_numerize)
text_return.append(number_to_input + 'M')
text_demo[idx + 1] = ""
elif token_next == "thousand" or token_next == "thousands":
if 'K' in number_numerize:
number_to_input = (number_to_input.translate({ord('K'): None}))
text_return.append(number_to_input + 'M')
elif 'M' in number_numerize:
number_to_input = (number_to_input.translate({ord('M'): None}))
text_return.append(number_to_input + 'B')
else:
text_return.append(number_to_input + 'K')
text_demo[idx + 1] = ""
elif 1000 > number > -1000:
text_return.append(number_numerize)
else:
text_return.append(number_numerize)
else:
text_return.append(number_numerize)
if 1900 < number < 2100 and help_minus == '':
if '~' in text_demo[idx]:
text_return.append(my_word)
else:
text_return.append(text_demo[idx])
return help_minus + ' '.join(text_return)
def ignore_emojis(self, text):
emoji_pattern = re.compile("["
u"\U0001F600-\U0001F64F" # emoticons
u"\U0001F300-\U0001F5FF" # symbols & pictographs
u"\U0001F680-\U0001F6FF" # transport & map symbols
u"\U0001F1E0-\U0001F1FF" # flags (iOS)
u"\U00002500-\U00002BEF" # chinese char
u"\U00002702-\U000027B0"
u"\U00002702-\U000027B0"
u"\U000024C2-\U0001F251"
u"\U0001f926-\U0001f937"
u"\U00010000-\U0010ffff"
u"\u2640-\u2642"
u"\u2600-\u2B55"
u"\u200d"
u"\u23cf"
u"\u23e9"
u"\u231a"
u"\ufe0f" # dingbats
u"\u3030"
"]+", flags=re.UNICODE)
ans = emoji_pattern.sub(r'', text)
return ans
def is_ascii(self, s):
ans = all(ord(c) < 128 or c == '…' or c == '’' or c == '³' or c == "¹⁹" for c in s)
return ans
def parse_percentage(self, string):
"""
change word to percent
100 percent -> 100%
:param string: string to check if there is a percent within
:return: array of converted strings
"""
return re.split('\s+', string)[0] + '%'
def remove_panctuation(self, word):
"""
remove pancuations from word (like . or , or : )
:param word
:return: word without panctuation
"""
# chars = set('.,:;!()[]{}?=+…$&')
if re.match(r'[^@]+@[^@]+\.[^@]+', word): return word
if "#" == word or "##" == word: return ""
if word[-2:] == "'s" or word[-2:] == "’s" or word[-2:] == "`s": word = word.replace(word[-2:], "")
smiles = [":)", ":(", ":-]", ":-)", ";)", ";-)", ":-(", ";(", ";-(", ":-P", ":P", ":p", ":-p"]
for smile in smiles:
if smile in word: word = word.replace(smile, "")
if word in smiles: return ''
if "\n" in word: word = word.replace("\n", " ")
if '#' in word and word[0] != '#': word = word.replace("#", "")
if '_' in word and '#' not in word:
word = word.replace("_", "")
if '@' in word and word[0] != '@': word = word.replace("@", "")
word = word.replace("-", " ")
word = word.replace("'", "")
word = re.sub(r'[€£€4️⃣“”‘‼⑥²⁸¹❶❷❽②⑦&$~’.,!…|?,…:;^"{}*=+()⁰\/[\[\]]', '', word)
return word
def get_name_and_entities(self, entities_url, array_text_space):
text = ""
for word in array_text_space:
if word == '' or word == '' or word[0] == '@' or word[0] == '#' or word == "RT": continue
text += word + " "
rx2 = re.compile(r'[A-Z][-a-zA-Z]+[1-9]*(?:\s+[A-Z][-a-zA-Z]+[1-9]*)*')
matches = rx2.findall(text)
tokinzed_entity_new = set()
i = 0
for i in range(len(matches)):
if len(str(matches[i]).split()) > 1:
tokinzed_entity_new.add(str(matches[i]))
i += 1
if "COVID 19" in text: tokinzed_entity_new.add("COVID 19")
if "Covid 19" in text: tokinzed_entity_new.add("Covid 19")
for word in tokinzed_entity_new:
if word.lower() not in self.stop_words:
all_places = [m.start() for m in re.finditer(word, text)]
self.array_names_and_entities[word] = all_places
return tokinzed_entity_new
def parse_doc(self, doc_as_list,stemmer=False):
"""
This function takes a tweet document as list and break it into different fields
:param doc_as_list: list re-preseting the tweet.
:return: Document object with corresponding fields.
"""
tweet_id = doc_as_list[0]
tweet_date = doc_as_list[1]
full_text = doc_as_list[2]
url = doc_as_list[3]
indices = doc_as_list[4]
retweet_text = doc_as_list[5]
retweet_url = doc_as_list[6]
retweet_indices = doc_as_list[7]
quote_text = doc_as_list[8]
quote_url = doc_as_list[9]
quote_indices = doc_as_list[10]
term_dict = {}
entities_local_dict = {}
array_url_parsed = []
url = str(url)
rt = False
if "RT" in full_text:
rt = True
if url != "{}" and "null" not in url:
dict2 = eval(url)
keys = dict2.keys()
for key in keys:
if dict2[key] != str("null") and "t.co" not in dict2[key]:
url_parsed = self.parse_url(dict2[key])
check = url_parsed.split()
for word in check:
array_url_parsed.append(word)
tokenized_text, names_and_entities = self.parse_sentence(full_text, stemmer=False)
doc_length = len(tokenized_text) # after text operations.
if doc_length == 0:
return None
for term in tokenized_text:
if len(term) < 2: continue
if stemmer:
term = self.porter_stemmer.stem(term)
if term not in term_dict.keys():
term_dict[term] = 1
else:
term_dict[term] += 1
for term in array_url_parsed:
if len(term) < 2: continue
if stemmer:
term = self.porter_stemmer.stem(term)
if term.lower() in self.stop_words or term == 'http' or term == 'https' or term == 'www':
continue
if term not in term_dict.keys():
term_dict[term] = 1
else:
term_dict[term] += 1
for term in names_and_entities.keys():
if len(term) < 2: continue
if term in self.stop_words:
continue
if term not in term_dict.keys():
term_dict[term] = 1
else:
term_dict[term] += 1
document = Document(tweet_id, tweet_date, full_text, url, retweet_text, retweet_url, quote_text,
quote_url, term_dict, len(self.array_names_and_entities), rt, doc_length)
return document