"""A basic example of using the SQLAlchemy Sharding API.
Sharding refers to horizontally scaling data across multiple
databases.

The basic components of a "sharded" mapping are:

* multiple databases, each assigned a 'shard id'
* a function which can return a single shard id, given an instance
  to be saved; this is called "shard_chooser"
* a function which can return a list of shard ids which apply to a particular
  instance identifier; this is called "id_chooser".  If it returns all shard ids,
  all shards will be searched.
* a function which can return a list of shard ids to try, given a particular 
  Query ("query_chooser").  If it returns all shard ids, all shards will be 
  queried and the results joined together.

In this example, four sqlite databases will store information about weather
data on a database-per-continent basis. We provide example shard_chooser,
id_chooser and query_chooser functions. The query_chooser illustrates
inspection of the SQL expression element in order to attempt to determine a
single shard being requested.

The construction of generic sharding routines is an ambitious approach
to the issue of organizing instances among multiple databases.   For a
more plain-spoken alternative, the "distinct entity" approach 
is a simple method of assigning objects to different tables (and potentially
database nodes) in an explicit way - described on the wiki at 
`EntityName <http://www.sqlalchemy.org/trac/wiki/UsageRecipes/EntityName>`_.

"""