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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 keywords(text):
 """get the top 10 keywords and their frequency scores ignores blacklisted words in stopWords, counts the number of occurrences of each word """

    text = split_words(text)
    numWords = len(text)  # of words before removing blacklist words
    freq = Counter(x for x in text if x not in stopWords)

    minSize = min(10, len(freq))  # get first 10
    keywords = {x: y for x, y in freq.most_common(minSize)}  # recreate a dict

    for k in keywords:
        articleScore = keywords[k]*1.0 / numWords
        keywords[k] = articleScore * 1.5 + 1

    return keywords