new_contents: #!/usr/bin/env python
  import json
  
  # Import the necessary methods from "twitter" library
  from twitter import Twitter, OAuth, TwitterHTTPError, TwitterStream
  
  # Variables that contains the user credentials to access Twitter API 
  ACCESS_TOKEN = '775072286617571328-XlgRWQiCCTGSAKjPmiYshuf6rGSXxYk'
  ACCESS_SECRET = 'sLbip6Oi3BHlq3hwcfMmF35PmJSm4cJZ4wYqmBql5N5ZP'
  CONSUMER_KEY = 'uoa6eO3G3U7gl8RVzB880WRQa'
  CONSUMER_SECRET = 'kKwSdpXJyF3Pn33cYn7yFOuagb9rFdvd39nTfcFfn6IZw7j8Wo'
  
  oauth = OAuth(ACCESS_TOKEN, ACCESS_SECRET, CONSUMER_KEY, CONSUMER_SECRET)
  
  # Initiate the connection to Twitter Streaming API
  twitStream = TwitterStream(auth=oauth)
  
  # Get a sample of the public data following through Twitter
  #iterator = twitter_stream.statuses.sample()
  iterator = twitStream.statuses.filter(track="#resolution", language="en")
  
  # Get data for my specific stream
  
  
  #twitter_userstream = TwitterStream(auth=oauth, domain='userstream.twitter.com')
  # Print each tweet in the stream to the screen 
  # Here we set it to stop after getting 1000 tweets. 
  # You don't have to set it to stop, but can continue running 
  # the Twitter API to collect data for days or even longer. 
  tweet_count = 10000000
  for tweet in iterator:
      tweet_count -= 1
      # Twitter Python Tool wraps the data returned by Twitter 
      # as a TwitterDictResponse object.
      # We convert it back to the JSON format to print/score
      print json.dumps(tweet)
  
      # The command below will do pretty printing for JSON data, try it out
      # print json.dumps(tweet, indent=4)
  
      if tweet_count <= 0:
          break
  
subject: Add Base Streaming API