input: Write a python function to compute sentiment scores for customer comments and add them to a dataframe column.
  assert compute_sentiment_scores(pd.DataFrame({'comment': ['I love this product!', 'This is the worst service ever.']})).equals(pd.DataFrame({'comment': ['I love this product!', 'This is the worst service ever.'], 'sentiment': [0.6696, -0.6696]}))
  assert compute_sentiment_scores(pd.DataFrame({'comment': ['Amazing experience.', 'Not happy with the quality.']})).equals(pd.DataFrame({'comment': ['Amazing experience.', 'Not happy with the quality.'], 'sentiment': [0.5859, -0.5574]}))
output: import pandas as pd
  from textblob import TextBlob
  
  def compute_sentiment_scores(df):
      def get_sentiment(comment):
          return TextBlob(comment).sentiment.polarity
      
      df['sentiment'] = df['comment'].apply(get_sentiment)
      return df