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https://github.com/enki/tragedy

A high-level Cassandra Object Abstraction for Python.
https://github.com/enki/tragedy

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A high-level Cassandra Object Abstraction for Python.

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# Tragedy

Tragedy 0.7-trunk by Paul Bohm  / @enkido on twitter.



A high-level Cassandra Object Abstraction for Python.



## In Development Warning



Tragedy currently only works with the latest Cassandra trunk checkouts (0.7). This code is already used in production, but still a moving target and expected to have bugs.



## Understanding Tragedy's Data Model



In Tragedy you build your data model from Models and Indexes. An abstract *Model* specifies the kind data that can be stored in a Model-Instance. We also call a Model-Instance a Row, since specific Model-Instances are uniquely identified by their unique RowKey. Knowing the Model and RowKey is all you need to store and retrieve data from Cassandra. The attributes of the Model correspond to the Columns of a Row. Each Column has a Field-Type like StringField or IntegerField. The RowKey decides which specific Row/Model-Instance the user is referring to and on which physical machine the data is stored. If you lose a RowKey, you can never store or retrieve that data again. Any Unicode string can be used as RowKey as long as it is unique among all Rows of a Model. If there's no naturally unique identifier for the data in a Row, you can ask Tragedy to generate a UUID-RowKey for you.



An *Index* is a special kind of Model with an unlimited number of Columns that all have the same Field-Type (usually ForeignKey). Indexes are used to map from one RowKey (e.g. an Username), to an ordered list of many others (e.g. a list of Blogposts). The Index is accessed with a RowKey, and doesn't store any data except for the ordered list of RowKeys to other Models.



Since distributed datastores like Cassandra don't support queries other than retrieving Models by RowKey, you have to create your Indexes when you write your data. By carefully tying Models and Indexes together, you can build complex but efficient applications that can run on large computing clusters.



Here's a simple example. Let's define and store a Tweet for a twitter-like application:

	class Tweet(Model):

    	uuid    = RowKey(autogenerate=True) # generate a UUID for us.

    	message = StringField()    

    	author  = ForeignKey(foreign_class=User, mandatory=True)



Tweet is a Model specification. If we instantiate Tweet, we get a specific tweet that we can write to the database:



    new_tweet = Tweet(message="Twittering from tragedy!", author='merlin')

	new_tweet.save()



Tweet instances are referred to and accessed by a RowKey. Tweet's RowKey is named `uuid` and its value is (randomly) autogenerated on the first save. Objects can only be retrieved from the datastore if their RowKey is known. Since Tweet's RowKey is random, we'll lose the Tweet if we don't keep a reference somehow. One way to do this, is to store the RowKey in an Index. Let's create an Index of all tweets a specific user posts:



	class TweetsSent(Index):

    	by_username = RowKey()

    	targetmodel = ForeignKey(foreign_class=Tweet, compare_with='TimeUUIDType')



	merlinIndex = TweetsSent(by_username='merlin')

	merlinIndex.append(new_tweet)

	merlinIndex.save()



TweetsSent is an abstract Index over Tweets sorted by Cassandra's TimeUUIDType. merlinIndex is a specifc TweetsSent-Index for user 'merlin', as specified by the given RowKey during instantiation. Items can be added to an Index using the .append() method, and changes to them saved using the .save() method. Just as with models, we can only retrieve Indexes whose RowKey we know. If we do, we can use .load() to load the index from the Database:



    tweets_by_user = TweetsSent(by_username='merlin').load()

	print tweets_by_user



The main difference between Indexes and Models is that Indexes keep track of an unlimited amount of ordered data of the same kind (normally ForeignKeys), whereas a Model keeps track of a limited number of data that can be any mixture of types. Indexes are most often used to to help us find Data whose RowKey we've forgotten. Models can refer to Indexes using ForeignKeys, and Indexes can refer to both Models and (less often) other Indexes. The call above gives us a list of Tweets previously posted by user 'merlin' with their RowKeys correctly set. However, since the Index only contains references the actual tweet data hasn't been loaded yet at this point. If we tried to work with those tweets, we'd see only empty tweets:



    })>

    

To actually load the tweets we need to resolve them (retrieve them using their RowKeys). Luckily Indexes have the .resolve() helper to make this easy:



	tweets_by_user.resolve()

	print tweets_by_user

    [}>]



Behind the scenes Index.resolve() almost works like calling Model.load() on all Tweets in the list. It's more efficient though, since this combines all required queries into one multiquery for faster processing. Now we've seen how to create tweets, store them, and find them again. If you want to see how you can distribute them to Followers, scroll down for a full example of a twitter-like application.



That's about it for the basics. There's more stuff Tragedy can do for you, like automatic validation that Tragedy and Cassandra agree on the Data Model, and the following example shows of some of them. Get in touch if you have questions!



## Installation

  $ setup.py install   (optionally --cassandra to install the compiled cassandra thrift bindings)



## IRC

Come hang out on #cassandra on irc.freenode.net.



## Example (full twitter-demo)



    from tragedy import *

    

    dev_cluster  = Cluster('Dev Cluster')

    twitty_keyspace = Keyspace('Twitty', dev_cluster)

    

    class User(Model):

        """A Model is stored and retrieved by its RowKey.

           Every Model has exactly one RowKey and one or more other Fields"""

        userid    = RowKey(autogenerate=True)

        username  = AsciiField()

        firstname = UnicodeField(mandatory=False)

        lastname  = UnicodeField(mandatory=False) # normally fields are mandatory

        password  = UnicodeField()

    

    class Tweet(Model):

        uuid    = RowKey(autogenerate=True) # generate a UUID for us.

        message = UnicodeField()    

        author  = ForeignKey(foreign_class=User, mandatory=True)

    

    class TweetsSent(Index):

    	by_username = RowKey()

    	targetmodel = ForeignKey(foreign_class=Tweet, compare_with='TimeUUIDType')

    

    def run():

        # Connect to cassandra

        twitty_keyspace.connect(servers=['localhost:9160'], auto_create_models=True, auto_drop_keyspace=True)

    

        dave = User(username='dave', firstname='dave', password='test').save()

        merlin = User(username='merlin', firstname='merlin', lastname='Bood', password='sunshine').save()

        peter = User(username='peter', firstname='Peter', password='secret').save()

    

        new_tweet = Tweet(author=dave, message='tweeting from tragedy').save()

        merlinIndex = TweetsSent(by_username=merlin['username'])

        merlinIndex.append(new_tweet)

        merlinIndex.save()

        

        tweets_by_user = TweetsSent(by_username='merlin').load()

        print tweets_by_user

        print list(tweets_by_user.resolve())

    

    if __name__ == '__main__':

        run()