code: def split_text(text, include_part_of_speech=False, strip_english=False, strip_numbers=False):
      u
  
      if not include_part_of_speech:
          seg_list = pseg.cut(text)
          if strip_english:
              seg_list = filter(lambda x: not contains_english(x), seg_list)
          if strip_numbers:
              seg_list = filter(lambda x: not _is_number(x), seg_list)
          return list(map(lambda i: i.word, seg_list))
      else:
          seg_list = pseg.cut(text)
          objs = map(lambda w: (w.word, w.flag), seg_list)
          if strip_english:
              objs = filter(lambda x: not contains_english(x[0]), objs)
          if strip_english:
              objs = filter(lambda x: not _is_number(x[0]), objs)
          return objs
  
      # if was_traditional:
      #   seg_list = map(tradify, seg_list)
  
      return list(seg_list)
docs: u"""
      Split Chinese text at word boundaries.
  
      include_pos: also returns the Part Of Speech for each of the words.
      Some of the different parts of speech are:
          r: pronoun
          v: verb
          ns: proper noun
          etc...
  
      This all gets returned as a tuple:
          index 0: the split word
          index 1: the word's part of speech
  
      strip_english: remove all entries that have English or numbers in them (useful sometimes)