from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer

# --- examples -------
sentences = [
    #easy tweet for VADER to understand
    "Lucky to be here at SWIFT 2017. #CS #Scottrules",
    #impossible to understand sarcasm
    "I'm having an awful day in the computer science building. JK I cant wait to work all day tomorrow too #blessed",
    #sometimes words have more than one meaning. VADER can't always understand these things
    "Learning about twitter analysis sure is great. I love python? #snakes"
             ]
scores = []
analyzer = SentimentIntensityAnalyzer()
for sentence in sentences:
    vs = analyzer.polarity_scores(sentence)
    print("{:-<95} {}".format(sentence, str(vs.get('compound'))))
    scores.append(vs.get('compound'))
print (scores)

#What kinds of conclusions could be made about tweets based off this information?
#How is the mood of a set of tweets important for making conclusions about the subjects of the tweets with specific hashtags?