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ML-For-Beginners/6-NLP/3-Translation-Sentiment/solution/book.py

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from textblob import TextBlob
# You should download the book text, clean it, and import it here
with open("pride.txt", encoding="utf8") as f:
file_contents = f.read()
book_pride = TextBlob(file_contents)
positive_sentiment_sentences = []
negative_sentiment_sentences = []
for sentence in book_pride.sentences:
if sentence.sentiment.polarity == 1:
positive_sentiment_sentences.append(sentence)
if sentence.sentiment.polarity == -1:
negative_sentiment_sentences.append(sentence)
print("The " + str(len(positive_sentiment_sentences)) + " most positive sentences:")
for sentence in positive_sentiment_sentences:
print("+ " + str(sentence.replace("\n", "").replace(" ", " ")))
print("The " + str(len(negative_sentiment_sentences)) + " most negative sentences:")
for sentence in negative_sentiment_sentences:
print("- " + str(sentence.replace("\n", "").replace(" ", " ")))