twitter_script.py

keywords = raw_input("Enter keywords with comma seperated :")
print "search keywords : " + keywords

# Import the necessary package to process data in JSON format
try:
    import json
except ImportError:
    import simplejson as 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 = '970879699629912064-J3LkOsWfQNYBVygkJ6l0vNa5APYJMjT'
ACCESS_SECRET = 'mqopj5kDosPWpzokH8VXvht7znHPlR1QwdcTntB9JilqM'
CONSUMER_KEY = 'v08rJASMheq0q0I4xZxDGmd6y'
CONSUMER_SECRET = 'ep9dtXFBoMUZRhmJdCmXbHJz3DrIlJmOJSf9Ch08oqQgr3TDix'

oauth = OAuth(ACCESS_TOKEN, ACCESS_SECRET, CONSUMER_KEY, CONSUMER_SECRET)

# Initiate the connection to Twitter Streaming API
twitter_stream = TwitterStream(auth=oauth)

# Get a sample of the public data following through Twitter
iterator = twitter_stream.statuses.filter(track=keywords, language="en", result_type="popular")

# 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 = 1000
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)
    if 'text' in tweet: # only messages contains 'text' field is a tweet
	print "{message : " + tweet['text'] + ", created_at : " + tweet['created_at'] + "}\n" # content of the 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