docs: def normalizer(text, exclusion=OPERATIONS_EXCLUSION, lower=True, separate_char='-', **kwargs):
      """
      Clean text string of simbols only alphanumeric chars.
      """
      clean_str = re.sub(r'[^\w{}]'.format(
          "".join(exclusion)), separate_char, text.strip()) or ''
      clean_lowerbar = clean_str_without_accents = strip_accents(clean_str)
  
      if '_' not in exclusion:
          clean_lowerbar = re.sub(r'\_', separate_char, clean_str_without_accents.strip())
  
      limit_guion = re.sub(r'\-+', separate_char, clean_lowerbar.strip())
  
      # TODO: refactor with a regexp
      if limit_guion and separate_char and separate_char in limit_guion[0]:
          limit_guion = limit_guion[1:]
  
      if limit_guion and separate_char and separate_char in limit_guion[-1]:
          limit_guion = limit_guion[:-1]
  
      if lower:
          limit_guion = limit_guion.lower()
  
      return limit_guion