text: # Twitter Sentiment Analysis using NLP
  
  # Install tweepy - pip install tweepy
  
  # Importing the libraries
  import tweepy
  import re
  import pickle
  
  from tweepy import OAuthHandler
  
  # Please change with your own consumer key, consumer secret, access token and access secret
  # Initializing the keys
  consumer_key = 'yoIwFkjZGYDa49aO16XqSNqcN'
  consumer_secret = 'gl4LQOItV7Z1aFwNrlvaiKJ3t8o8h99blMIAmnmdHxYjzjRAxO' 
  access_token = '624310916-E7fDF2IE8P6bfY1oVFglASf6F8RnxMd3vgSXFqnZ'
  access_secret ='ID9JcoXHsDcKtvNcnmBGcCQhUlO0wmwAxBJ6LCesiUAas'
  
  # Initializing the tokens
  auth = OAuthHandler(consumer_key, consumer_secret)
  auth.set_access_token(access_token, access_secret)
  args = ['trump'];
  api = tweepy.API(auth,timeout=10)
  
  # Fetching the tweets
  list_tweets = []
  
  query = args[0]
  if len(args) == 1:
      for status in tweepy.Cursor(api.search,q=query+" -filter:retweets",lang='en',result_type='recent',geocode="22.1568,89.4332,500km").items(100):
          list_tweets.append(status.text)
          
  # Loading the vectorizer and classfier
  with open('classifier.pickle','rb') as f:
      classifier = pickle.load(f)
      
  with open('tfidfmodel.pickle','rb') as f:
      tfidf = pickle.load(f)    
  