new_contents: import sys
  
  sentimentData = 'wordwithStrengthtxt.txt'
  twitterData = 'input.txt'
  
  #var will take the user input 
  var = raw_input("Enter something: ")
  
  def tweet_dict(twitterData):
      ''' (file) -> list of dictionaries
  This method should take your output.txt
  file and create a list of dictionaries.
  '''
      twitter_list_dict = []
      #storing the user given sentance to the dictionary for the classification
      twitter_list_dict.extend([var])
      #twitter_list_dict = ["it is good not bad","good movie i love it", "hate this, really hate this movie"] you can use this if you want to work with direct list with data
      return twitter_list_dict
     
      
  def sentiment_dict(sentimentData):
      ''' (file) -> dictionary
  This method should take your sentiment file
  and create a dictionary in the form {word: value}
  '''
      afinnfile = open(sentimentData)
      scores = {} # initialize an empty dictionary
      for line in afinnfile:
          term, score = line.split("\t") # The file is tab-delimited. "\t" means "tab character"
          scores[term] = float(score) # Convert the score to an integer.
  
      return scores # Print every (term, score) pair in the dictionary
      
  def main():
      
      
      tweets = tweet_dict(twitterData)
      sentiment = sentiment_dict(sentimentData)
      
      '''Create a method below that loops through each tweet in your
  twees_list. For each individual tweet it should add up you sentiment
  score, based on the sent_dict.
  '''
      for index in range(len(tweets)):
          tweet_word = tweets[index].split()
          sent_score = 0
          for word in tweet_word:
              word = word.rstrip('?:!.,;"!@')
              word = word.replace("\n", "")
              
              if word in sentiment.keys():
                  sent_score = sent_score + float(sentiment[word])
                      
              else:
                  sent_score = sent_score
          if float(sent_score) > 0:
               print tweets[index]
               if float(sent_score) > 0.7:
                   print sent_score
                   print 'Highly Positive Sentiment'
               else:
                  print sent_score
                  print 'Positive Sentiment'
               
               
          if float(sent_score) < 0:
              print tweets[index]
              if float(sent_score) < -0.7:
                   print sent_score
                   print 'Highly Negative Sentiment'
              else:
                   print sent_score
                   print 'Negative Sentiment'
  
  
          if float(sent_score) == 0:
              print tweets[index]
              print 'Neutral Sentiment'
     
  if __name__ == '__main__':
      main()
  
subject: Create sentimentstrength.py