Scalability-centric object document mapper for Mongo on Python
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README.rst

ScalyMongo

Author: Allan Caffee <allan.caffee@gmail.com>

About

The ScalyMongo package is a set of tools to simplify the development of large scale distributed software utilizing MongoDB.

Project Status

ScalyMongo is still in Pre-Alpha development and is not yet ready to be deployed in the wild.

Key Priciples

ScalyMongo is intended to help developers in the following ways:

  • scalability: ScalyMongo makes it easy to write software intended to work efficiently on sharded MongoDB deployments. Internal checks warn developers when their queries or inserts are liable to perform poorly on sharded collections.
  • simplicity: ScalyMongo makes interacting with your documents easier by providing a simple Python-friendly document interface.
  • flexibility: ScalyMongo doesn't try to be everything for everyone. Where necessary users can interact directly with the underlying PyMongo driver.

Getting Started

Below is simple example of a sharded collection of blog posts

>>> from scalymongo import Document, Connection
>>> class BlogPost(Document):
...     structure = {
...        'author': basestring,
...        'title': basestring,
...        'body': basestring,
...        'unique_views': int,
...        'comments': [{
...            'author': basestring,
...            'comment': basestring,
...            'rank': int,
...        }],
...     }
...     indexes = [{
...         'fields': ['author', 'title'],
...         'shard_key': True,
...         'unique': True,
...     }]
...     __database__ = 'blog'
...     __collection__ = 'blog_posts'
...

The example above describes the structure for a blog post. Notice that we declared a unique index on the author and title fields. The index hasn't actually been created yet, but knowing what indexes exist allow ScalyMongo to warn you about potentially poor choices in queries. Also notice that we declared this index to be used as the shard key.

Now that we've got a simple document class let's create a sample post.

>>> conn = Connection("localhost", 27017)
>>> post = conn.models.BlogPost()
>>> post['author'] = 'Allan'
>>> post['title'] = 'My first post'
>>> post['body'] = "Well, I don't actually have anything to write about..."
>>> post.save()

Great! Now we've got our first blog post. Now let's look Allan's post up to make sure it was really saved.

>>> conn.models.BlogPost.find_one({'author': 'Allan'})
Traceback (most recent call last):
  ...
scalymongo.errors.GlobalQueryException: Some or all of the shard key was not specified.  Missing fields were title.

What happended!? Remember that we declared a shard key on the author and title fields? ScalyMongo noticed that we trying to query without having the full shard key. This means that the query might potentially have to hit every shard in our cluster to find the one document we were looking for. That's probably not what we wanted to do, and it certainly wouldn't be something we would want to occur on a regular basis in a production cluster. Let's refine our query a bit so that it doesn't hit every shard.

>>> conn.models.BlogPost.find_one({'author': 'Allan', 'title': 'My first post'})
{u'_id': ObjectId('4deb90e41717953527000000'),
 u'author': u'Allan',
 u'body': u"Well, I don't actually have anything to write about...",
 u'title': u'My first post'}

And sure enough that's our first post. Of course sometimes we really do want to find something even if we don't have the full shard key. Sometimes this is useful during development to look up documents from the interactive console. We can just override ScalyMongo's recomendations and force the query anyway:

>>> conn.models.BlogPost.find_one({'author': 'Allan'}, allow_global=True)
{u'_id': ObjectId('4deb90e41717953527000000'),
 u'author': u'Allan',
 u'body': u"Well, I don't actually have anything to write about...",
 u'title': u'My first post'}

Take that best practices!

Well that's it for our basic overview of ScalyMongo. Coming soon is a more in-depth introduction.

Special Thanks

ScalyMongo was heavily influenced by the semantics and interface of the popular database framework MongoKit. Special thanks go to Namlook and all of the developers who have contributed to MongoKit.