Optimization: Dumping JSON from a Streaming API to Mongo

Background: I have a python module set up to grab JSON objects from a streaming API and store them (bulk insert of 25 at a time) in MongoDB using pymongo. For comparison, I also have a bash command to curl from the same streaming API and pipe it to mongoimport. Both these approaches store data in separate collections.

Periodically, I monitor the count() of the collections to check how they fare.

So far, I see the python module lagging by about 1000 JSON objects behind the curl | mongoimport approach.

Problem: How can I optimize my python module to be ~ in sync with the curl | mongoimport?

I cannot use tweetstream since I am not using the Twitter API but a 3rd party streaming service.

Could someone please help me out here?

Python module:

class StreamReader:
    def __init__(self):
        try:
            self.buff = ""
            self.tweet = ""
            self.chunk_count = 0
            self.tweet_list = []
            self.string_buffer = cStringIO.StringIO()
            self.mongo = pymongo.Connection(DB_HOST)
            self.db = self.mongo[DB_NAME]
            self.raw_tweets = self.db["raw_tweets_gnip"]
            self.conn = pycurl.Curl()
            self.conn.setopt(pycurl.ENCODING, 'gzip')
            self.conn.setopt(pycurl.URL, STREAM_URL)
            self.conn.setopt(pycurl.USERPWD, AUTH)
            self.conn.setopt(pycurl.WRITEFUNCTION, self.handle_data)
            self.conn.perform()
        except Exception as ex:
            print "error ocurred : %s" % str(ex)

    def handle_data(self, data):
        try:
            self.string_buffer = cStringIO.StringIO(data)
            for line in self.string_buffer:
                try:
                    self.tweet = json.loads(line)