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authorMike Bayer <mike_mp@zzzcomputing.com>2012-07-28 17:05:50 -0400
committerMike Bayer <mike_mp@zzzcomputing.com>2012-07-28 17:05:50 -0400
commit22ba1c43b792953ae6f791512d276739c8c09eae (patch)
treebdf9f639b01426a8a2e1c8c61d35533026dd4265 /examples/sharding/__init__.py
parent27913554a85c308d81e6c018669d0246ceecc639 (diff)
downloadsqlalchemy-22ba1c43b792953ae6f791512d276739c8c09eae.tar.gz
-whitespace bonanza, contd
Diffstat (limited to 'examples/sharding/__init__.py')
-rw-r--r--examples/sharding/__init__.py8
1 files changed, 4 insertions, 4 deletions
diff --git a/examples/sharding/__init__.py b/examples/sharding/__init__.py
index d4b463949..dacc815f9 100644
--- a/examples/sharding/__init__.py
+++ b/examples/sharding/__init__.py
@@ -10,8 +10,8 @@ The basic components of a "sharded" mapping are:
* 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
+* 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
@@ -22,9 +22,9 @@ 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
+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
+database nodes) in an explicit way - described on the wiki at
`EntityName <http://www.sqlalchemy.org/trac/wiki/UsageRecipes/EntityName>`_.
"""