textblob_predict.py

class TextBlobSentiment(Base):
    """Predict fine-grained sentiment classes using TextBlob."""
    def __init__(self, model_file: str=None) -> None:
        super().__init__()

    def score(self, text: str) -> float:
        # pip install textblob
        from textblob import TextBlob
        return TextBlob(text).sentiment.polarity

    def predict(self, train_file: None, test_file: str, lower_case: bool) -> pd.DataFrame:
        df = self.read_data(test_file, lower_case)
        df['score'] = df['text'].apply(self.score)
        # Convert float score to category based on binning
        df['pred'] = pd.cut(df['score'],
                            bins=5,
                            labels=[1, 2, 3, 4, 5])
        df = df.drop('score', axis=1)
        return df