# Streaming With Tweepy

Tweepy makes it easier to use the twitter streaming api by handling authentication, connection, creating and destroying the session, reading incoming messages, and partially routing messages.

This page aims to help you get started using Twitter streams with Tweepy by offering a first walk through. Some features of Tweepy streaming are not covered here. See streaming.py in the Tweepy source code.

API authorization is required to access Twitter streams. Follow the Authentication Tutorial if you need help with authentication.

## Summary

The Twitter streaming API is used to download twitter messages in real time. It is useful for obtaining a high volume of tweets, or for creating a live feed using a site stream or user stream. See the Twitter Streaming API Documentation.

The streaming api is quite different from the REST api because the REST api is used to pull data from twitter but the streaming api pushes messages to a persistent session. This allows the streaming api to download more data in real time than could be done using the REST API.

In Tweepy, an instance of tweepy.Stream establishes a streaming session and routes messages to StreamListener instance. The on_data method of a stream listener receives all messages and calls functions according to the message type. The default StreamListener can classify most common twitter messages and routes them to appropriately named methods, but these methods are only stubs.

Therefore using the streaming api has three steps.

1. Create a class inheriting from StreamListener
2. Using that class create a Stream object
3. Connect to the Twitter API using the Stream.

## Step 1: Creating a StreamListener

This simple stream listener prints status text. The on_data method of Tweepy’s StreamListener conveniently passes data from statuses to the on_status method. Create class MyStreamListener inheriting from StreamListener and overriding on_status.:

    import tweepy
    #override tweepy.StreamListener to add logic to on_status
    class MyStreamListener(tweepy.StreamListener):

        def on_status(self, status):
            print(status.text)

## Step 2: Creating a Stream

We need an api to stream. See Authentication Tutorial to learn how to get an api object. Once we have an api and a status listener we can create our stream object.:

    myStreamListener = MyStreamListener()
    myStream = tweepy.Stream(auth = api.auth, listener=myStreamListener())

## Step 3: Starting a Stream

A number of twitter streams are available through Tweepy. Most cases will use filter, the user_stream, or the sitestream. For more information on the capabilities and limitations of the different streams see Twitter Streaming API Documentation.

In this example we will use filter to stream all tweets containing the word python. The track parameter is an array of search terms to stream.

    myStream.filter(track=['python'])

## A Few More Pointers

### Async Streaming

Streams not terminate unless the connection is closed, blocking the thread. Tweepy offers a convenient async parameter on filter so the stream will run on a new thread. For example

    myStream.filter(track=['python'], async=True)

### Handling Errors

When using Twitter’s streaming API one must be careful of the dangers of rate limiting. If clients exceed a limited number of attempts to connect to the streaming API in a window of time, they will receive error 420. The amount of time a client has to wait after receiving error 420 will increase exponentially each time they make a failed attempt.

Tweepy’s Stream Listener usefully passes error messages to an on_error stub. We can use on_error to catch 420 errors and disconnect our stream.

    class MyStreamListener(tweepy.StreamListener):

        def on_error(self, status_code):
            if status_code == 420:
                #returning False in on_data disconnects the stream
                return False

For more information on error codes from the twitter api see Twitter Response Codes Documentation.