nampnq / stream-framework

Stream Framework is a Python library, which allows you to build newsfeed and notification systems using Cassandra and/or Redis.

Stream Framework (previously Feedly)

Note

This project was previously named Feedly. As requested by feedly.com we have now renamed the project to Stream Framework. You can find more details about the name change on the blog.

Activity Streams & Newsfeeds

Stream Framework allows you to build activity streams & newsfeeds using Cassandra and/or Redis. Examples of what you can build are:

• Activity streams such as seen on Github
• A Twitter style newsfeed
• A feed like Instagram/ Pinterest
• Facebook style newsfeeds
• A notification system

(Feeds are also commonly called: Activity Streams, activity feeds, news streams.)

Example application

We've included a [Pinterest like example application] example_app_link based on Stream Framework.

GetStream.io

Stream Framework's authors also offer a Saas solution for building feed systems at [getstream.io] stream The hosted service is highly optimized and allows you start building your application immediatly. It saves you the hassle of maintaining Cassandra, Redis, Faye, RabbitMQ and Celery workers. Clients are available for [Node] stream_js, [Ruby] stream_ruby, [Python] stream_python and [PHP] stream_php

Consultancy

For Stream Framework and GetStream.io consultancy please contact thierry at getstream.io

Authors

• Thierry Schellenbach (thierry at getstream.io)
• Tommaso Barbugli (tommaso at getstream.io)
• Guyon Morée

Resources

• Documentation
• Bug Tracker
• Code
• Travis CI

Tutorials

• [Pinterest style feed example app] mellowmorning_example

Using Stream Framework

This quick example will show you how to publish a Pin to all your followers. So lets create an activity for the item you just pinned.

from stream_framework.activity import Activity


def create_activity(pin):
    activity = Activity(
        pin.user_id,
        PinVerb,
        pin.id,
        pin.influencer_id,
        time=make_naive(pin.created_at, pytz.utc),
        extra_context=dict(item_id=pin.item_id)
    )
    return activity

Next up we want to start publishing this activity on several feeds. First of all we want to insert it into your personal feed, and then into your followers' feeds. Lets start by defining these feeds.

from stream_framework.feeds.redis import RedisFeed


class UserPinFeed(PinFeed):
    key_format = 'feed:user:%(user_id)s'


class PinFeed(RedisFeed):
    key_format = 'feed:normal:%(user_id)s'

Writing to these feeds is very simple. For instance to write to the feed of user 13 one would do

feed = UserPinFeed(13)
feed.add(activity)

But we don't want to publish to just one users feed. We want to publish to the feeds of all users which follow you. This action is called a fanout and is abstracted away in the manager class. We need to subclass the Manager class and tell it how we can figure out which user follow us.

from stream_framework.feed_managers.base import Manager


class PinManager(Manager):
    feed_classes = dict(
        normal=PinFeed,
    )
    user_feed_class = UserPinFeed
    
    def add_pin(self, pin):
        activity = pin.create_activity()
        # add user activity adds it to the user feed, and starts the fanout
        self.add_user_activity(pin.user_id, activity)

    def get_user_follower_ids(self, user_id):
        ids = Follow.objects.filter(target=user_id).values_list('user_id', flat=True)
        return {FanoutPriority.HIGH:ids}
    
manager = PinManager()

Now that the manager class is setup broadcasting a pin becomes as easy as

manager.add_pin(pin)

Calling this method wil insert the pin into your personal feed and into all the feeds of users which follow you. It does so by spawning many small tasks via Celery. In Django (or any other framework) you can now show the users feed.

# django example

@login_required
def feed(request):
    '''
    Items pinned by the people you follow
    '''
    context = RequestContext(request)
    feed = manager.get_feeds(request.user.id)['normal']
    activities = list(feed[:25])
    context['activities'] = activities
    response = render_to_response('core/feed.html', context)
    return response

This example only briefly covered how Stream Framework works. The full explanation can be found on read the docs.

Features

Stream Framework uses celery and Redis/Cassandra to build a system with heavy writes and extremely light reads. It features:

• Asynchronous tasks (All the heavy lifting happens in the background, your users don't wait for it)
• Reusable components (You will need to make tradeoffs based on your use cases, Stream Framework doesnt get in your way)
• Full Cassandra and Redis support
• The Cassandra storage uses the new CQL3 and Python-Driver packages, which give you access to the latest Cassandra features.
• Built for the extremely performant Cassandra 2.0

Background Articles

A lot has been written about the best approaches to building feed based systems. Here's a collection on some of the talks:

[Twitter 2013] twitter_2013 Redis based, database fallback, very similar to Fashiolista's old approach.

[Etsy feed scaling] etsy (Gearman, separate scoring and aggregation steps, rollups - aggregation part two)

[Facebook history] facebook

[Django project with good naming conventions] djproject

[Activity stream specification] activity_stream

[Quora post on best practises] quora

[Quora scaling a social network feed] quora2

[Redis ruby example] redisruby

[FriendFeed approach] friendfeed

[Thoonk setup] thoonk

[Yahoo Research Paper] yahoo

[Twitter’s approach] twitter

[Cassandra at Instagram] instagram