gpt2-medium-persian / src /normalizer.py
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import hazm
import re
import string
from regexes.currency import CURRENCY_REGEX
from regexes.email import EMAIL_REGEX
from regexes.latin import LATIN_REGEX
from regexes.latin import LATIN_REGEX, LATIN_WITH_SPECIAL_REGEX
from regexes.number import NUMBERS_REGEX
from regexes.phone import PHONE_REGEX
from regexes.quote import DOUBLE_QUOTE_REGEX, SINGLE_QUOTE_REGEX
from regexes.url import URL_REGEX
from regexes.persian import PERSIAN_REGEX
from regexes.punk import PUNK_REGEX
import dictionary
allowed_char = string.ascii_letters + string.digits + ':/@_-. '
def make_trans(list_a, list_b):
return dict((ord(a), b) for a, b in zip(list_a, list_b))
def multiple_replace(text, chars_to_mapping):
pattern = "|".join(map(re.escape, chars_to_mapping.keys()))
return re.sub(pattern, lambda m: chars_to_mapping[m.group()], str(text))
def remove_adv_by_tag_name(text, tag_name):
found = text.find(tag_name)
if found > 0:
text = text[:found]
return text
def clean_url(text):
# removing html tags
text = re.sub('<.*?>', '', text)
# removing normal(without space urls)
text = re.sub(r'(?:(?:http|https):\/\/)?([-a-zA-Z0-9.]{2,256}\.[a-z]{2,4})\b(?:\/[-a-zA-Z0-9@:%_\+.~#?&//=]*)?', "",
text)
# removing urls that contains space
result = ''
for char in text:
if char in allowed_char:
result += char
result = result.replace(' ', '')
result = result.split(':')
for phrase in result:
p = phrase
if '//' in p:
if ('https :' + p) in text:
text = text.replace('https :' + p, '')
elif ('http :' + p) in text:
text = text.replace('http :' + p, '')
elif '@' in p:
if p in text:
text = text.replace(p, '')
return text
ar2fa_digits = make_trans("٠١٢٣٤٥٦٧٨٩٪", "۰۱۲۳۴۵۶۷۸۹٪")
fa2en_digits = make_trans("۰۱۲۳۴۵۶۷۸۹٪", "0123456789%")
normalizer = hazm.Normalizer(persian_numbers=True, punctuation_spacing=False)
def normalize(text, zwnj="\u200c", tokenized=False):
text = text.replace("\n", " ").replace("\t", " ")
text = re.sub(r"\u200c+", "\u200c", text)
text = text.replace('ـ', '')
text = normalizer.normalize(text)
if len(dictionary.characters) > 0:
text = multiple_replace(text, dictionary.characters)
if len(dictionary.words_map) > 0:
text = multiple_replace(text, dictionary.words_map)
text = text.translate(ar2fa_digits)
text = text.translate(fa2en_digits)
text = SINGLE_QUOTE_REGEX.sub("'", text)
text = DOUBLE_QUOTE_REGEX.sub('"', text)
text = CURRENCY_REGEX.sub(r" \1 ", text)
text = clean_url(text)
text = remove_adv_by_tag_name(text, tag_name="برچسب ها :")
text = URL_REGEX.sub(" ", text)
text = EMAIL_REGEX.sub(" ", text)
text = PHONE_REGEX.sub(r" \1 ", text)
text = NUMBERS_REGEX.sub(r" \1 ", text)
text = LATIN_REGEX.sub(r" \1 ", text)
# text = PUNK_REGEX.sub(r" \1 ", text) # must be remained the same!
# Allow only english and persian characters
text = re.sub(PERSIAN_REGEX, " ", text)
text = text.replace(f" {zwnj} ", f"{zwnj}")
text = text.replace(f"{zwnj} ", f"{zwnj}")
text = text.replace(f" {zwnj}", f"{zwnj}")
if len(dictionary.special_tokens) > 0:
text = multiple_replace(text, dictionary.special_tokens)
tokens = []
for token in text.split():
token = token.strip()
if token:
if token.startswith(zwnj) and token.endswith(zwnj):
token = token[1:-1]
if token.startswith(zwnj):
token = token[1:]
elif token.endswith(zwnj):
token = token[:-1]
else:
token = token
tokens.append(token)
if tokenized:
return tokens
return " ".join(tokens)
if __name__ == '__main__':
import textwrap
# input_text = " «هفتاد سی» "
# input_text = normalize(input_text)
# input_text = DOUBLE_QUOTE_REGEX.sub('"', input_text)
# print(textwrap.fill(input_text))
# print(normalize(input_text, tokenized=True))