code: def normalize_list(text):
      
      pieces = [morphy_stem(word) for word in tokenize(text)]
      pieces = [piece for piece in pieces if good_lemma(piece)]
      if not pieces:
          return [text]
      if pieces[0] == 'to':
          pieces = pieces[1:]
      return pieces
docs: Get a list of word stems that appear in the text. Stopwords and an initial
      'to' will be stripped, unless this leaves nothing in the stem.
  
      >>> normalize_list('the dog')
      ['dog']
      >>> normalize_list('big dogs')
      ['big', 'dog']
      >>> normalize_list('the')
      ['the']