"func.current_timestamp()" is registered as returning a DATETIME type in
SQLAlchemy, so this function still receives SQLAlchemy-level result processing.
-Pooling Behavior
-------------------
-
-Pysqlite connections do not support being moved between threads, unless
-the ``check_same_thread`` Pysqlite flag is set to ``False``. In addition,
-when using an in-memory SQLite database, the full database exists only within
-the scope of a single connection. It is reported that an in-memory
-database does not support being shared between threads regardless of the
-``check_same_thread`` flag - which means that a multithreaded
-application **cannot** share data from a ``:memory:`` database across threads
-unless access to the connection is limited to a single worker thread which communicates
-through a queueing mechanism to concurrent threads.
-
-To provide for these two behaviors, the pysqlite dialect will select a :class:`.Pool`
-implementation suitable:
-
-* When a ``:memory:`` SQLite database is specified, the dialect will use :class:`.SingletonThreadPool`.
- This pool maintains a single connection per thread, so that all access to the engine within
- the current thread use the same ``:memory:`` database.
-* When a file-based database is specified, the dialect will use :class:`.NullPool` as the source
- of connections. This pool closes and discards connections which are returned to the pool immediately.
- SQLite file-based connections have extermely low overhead, so pooling is not necessary.
- The scheme also prevents a connection from being used again in a different thread
- and works best with SQLite's coarse-grained file locking.
+Threading/Pooling Behavior
+---------------------------
+
+Pysqlite's default behavior is to prohibit the usage of a single connection
+in more than one thread. This is controlled by the ``check_same_thread``
+Pysqlite flag. This default is intended to work with older versions
+of SQLite that did not support multithreaded operation under
+various circumstances. In particular, older SQLite versions
+did not allow a ``:memory:`` database to be used in multiple threads
+under any circumstances.
+
+SQLAlchemy sets up pooling to work with Pysqlite's default behavior:
+
+* When a ``:memory:`` SQLite database is specified, the dialect by default will use
+ :class:`.SingletonThreadPool`. This pool maintains a single connection per
+ thread, so that all access to the engine within the current thread use the
+ same ``:memory:`` database - other threads would access a different
+ ``:memory:`` database.
+* When a file-based database is specified, the dialect will use :class:`.NullPool`
+ as the source of connections. This pool closes and discards connections
+ which are returned to the pool immediately. SQLite file-based connections
+ have extremely low overhead, so pooling is not necessary. The scheme also
+ prevents a connection from being used again in a different thread and works
+ best with SQLite's coarse-grained file locking.
.. note:: The default selection of :class:`.NullPool` for SQLite file-based databases
is new in SQLAlchemy 0.7. Previous versions
select :class:`.SingletonThreadPool` by
default for all SQLite databases.
+Modern versions of SQLite no longer have the threading restrictions, and assuming
+the sqlite3/pysqlite library was built with SQLite's default threading mode
+of "Serialized", even ``:memory:`` databases can be shared among threads.
+
+To use a ``:memory:`` database in a multithreaded scenario, the same connection
+object must be shared among threads, since the database exists
+only within the scope of that connection. The :class:`.StaticPool` implementation
+will maintain a single connection globally, and the ``check_same_thread`` flag
+can be passed to Pysqlite as ``False``::
+
+ from sqlalchemy.pool import StaticPool
+ engine = create_engine('sqlite://',
+ connect_args={'check_same_thread':False},
+ poolclass=StaticPool)
+
+Note that using a ``:memory:`` database in multiple threads requires a recent
+version of SQLite.
+
Unicode
-------