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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def normalize_list(text):
 """ 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. ['dog'] ['big', 'dog'] ['the'] """

    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