code: import sys
  from tweepy.streaming import StreamListener
  from tweepy import OAuthHandler
  from tweepy import Stream
  import twitter_credentials
  
  """Tweepy module is used to stream live tweets directly from Twitter in real-time. 
  The tweets are visualized and then the TextBlob module is used to do sentiment analysis on the tweets."""
  from tweepy import API 
  from tweepy import Cursor
  from tweepy.streaming import StreamListener
  from tweepy import OAuthHandler
  from tweepy import Stream
  import numpy as np
  import pandas as pd
  
  
  # # # # TWITTER CLIENT # # # #
  class TwitterClient():
      def __init__(self, twitter_user=None):
          self.auth = TwitterAuthenticator().authenticate_twitter_app()
          self.twitter_client = API(self.auth)
  
          self.twitter_user = twitter_user
  
      def get_twitter_client_api(self):
          return self.twitter_client
  
      def get_user_timeline_tweets(self, num_tweets):
          tweets = []
          for tweet in Cursor(self.twitter_client.user_timeline, id=self.twitter_user).items(num_tweets):
              tweets.append(tweet)
          return tweets
  
      def get_friend_list(self, num_friends):
          friend_list = []
          for friend in Cursor(self.twitter_client.friends, id=self.twitter_user).items(num_friends):
              friend_list.append(friend)
          return friend_list
  
      def get_home_timeline_tweets(self, num_tweets):
          home_timeline_tweets = []
          for tweet in Cursor(self.twitter_client.home_timeline, id=self.twitter_user).items(num_tweets):
              home_timeline_tweets.append(tweet)
          return home_timeline_tweets
  
  
  # # # # TWITTER AUTHENTICATER # # # #
  class TwitterAuthenticator():
  
      def authenticate_twitter_app(self):
          auth = OAuthHandler(twitter_credentials.CONSUMER_KEY, twitter_credentials.CONSUMER_SECRET)
          auth.set_access_token(twitter_credentials.ACCESS_TOKEN, twitter_credentials.ACCESS_TOKEN_SECRET)
          return auth
  
  # # # # TWITTER STREAMER # # # #
  class TwitterStreamer():
      """
      Class for streaming and processing live tweets.
      """
      def __init__(self):
          self.twitter_autenticator = TwitterAuthenticator()    
  
      def stream_tweets(self, fetched_tweets_filename, hash_tag_list):
          # This handles Twitter authetification and the connection to Twitter Streaming API
          listener = TwitterListener(fetched_tweets_filename)
          auth = self.twitter_autenticator.authenticate_twitter_app() 
          stream = Stream(auth, listener)
  
          # This line filter Twitter Streams to capture data by the keywords: 
          stream.filter(track=hash_tag_list)
  
  
  # # # # TWITTER STREAM LISTENER # # # #
  class TwitterListener(StreamListener):
      """
      This is a basic listener that just prints received tweets to stdout.
      """
      def __init__(self, fetched_tweets_filename):
          self.fetched_tweets_filename = fetched_tweets_filename
  
      def on_data(self, data):
          try:
              print(data)
              with open(self.fetched_tweets_filename, 'a') as tf:
                  tf.write(data)
              return True
          except BaseException as e:
              print("Error on_data %s" % str(e))
          return True
            
      def on_error(self, status):
          if status == 420:
              # Returning False on_data method in case rate limit occurs.
              return False
          print(status)
  
  
  class TweetAnalyzer():
      """
      Functionality for analyzing and categorizing content from tweets.
      """
      def tweets_to_data_frame(self, tweets):
          df = pd.DataFrame(data=[tweet.text for tweet in tweets], columns=['Tweets'])
  
          df['id'] = np.array([tweet.id for tweet in tweets])
          df['len'] = np.array([len(tweet.text) for tweet in tweets])
          df['date'] = np.array([tweet.created_at for tweet in tweets])
          df['source'] = np.array([tweet.source for tweet in tweets])
          df['likes'] = np.array([tweet.favorite_count for tweet in tweets])
          df['retweets'] = np.array([tweet.retweet_count for tweet in tweets])
  
          return df
  
   
  if __name__ == '__main__':
  
      twitter_client = TwitterClient()
      tweet_analyzer = TweetAnalyzer()
  
      api = twitter_client.get_twitter_client_api()
  
      tweets = api.user_timeline(screen_name="realDonaldTrump", count=20)
  
      #print(dir(tweets[0]))
      #print(tweets[0].retweet_count)
  
      df = tweet_analyzer.tweets_to_data_frame(tweets)
      
      print(df.head(10))
apis: numpy.array pandas.DataFrame