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"""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>`_.
.. autosource::
"""
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