# sentiment_analyzer.py

from nltk.sentiment.vader import SentimentIntensityAnalyzer

# Initialize the VADER sentiment intensity analyzer
# We only need to create one instance of this.
_analyzer = SentimentIntensityAnalyzer()

def get_sentiment_score(text):
    """
    Analyzes a piece of text and returns its sentiment score.
    
    The 'compound' score is a single metric that summarizes the sentiment.
    It ranges from -1 (most negative) to +1 (most positive).
    """
    # The polarity_scores() method returns a dictionary with 'neg', 'neu', 'pos', and 'compound' scores.
    # We are most interested in the 'compound' score.
    scores = _analyzer.polarity_scores(text)
    return scores['compound']