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Update SQLAlchemy

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This commit is contained in:
Ruud
2013-06-14 11:00:06 +02:00
parent 267ecfacab
commit 4aa6700ceb
124 changed files with 6500 additions and 5207 deletions
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libs/sqlalchemy/dialects/sqlite/pysqlite.py
+34 -31
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@@ -1,5 +1,5 @@
# sqlite/pysqlite.py
# Copyright (C) 2005-2012 the SQLAlchemy authors and contributors <see AUTHORS file>
# Copyright (C) 2005-2013 the SQLAlchemy authors and contributors <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: http://www.opensource.org/licenses/mit-license.php
@@ -12,15 +12,15 @@ module included with the Python distribution.
Driver
------
When using Python 2.5 and above, the built in ``sqlite3`` driver is
When using Python 2.5 and above, the built in ``sqlite3`` driver is
already installed and no additional installation is needed. Otherwise,
the ``pysqlite2`` driver needs to be present. This is the same driver as
``sqlite3``, just with a different name.
The ``pysqlite2`` driver will be loaded first, and if not found, ``sqlite3``
is loaded. This allows an explicitly installed pysqlite driver to take
precedence over the built in one. As with all dialects, a specific
DBAPI module may be provided to :func:`~sqlalchemy.create_engine()` to control
precedence over the built in one. As with all dialects, a specific
DBAPI module may be provided to :func:`~sqlalchemy.create_engine()` to control
this explicitly::
from sqlite3 import dbapi2 as sqlite
@@ -64,25 +64,25 @@ The sqlite ``:memory:`` identifier is the default if no filepath is present. Sp
Compatibility with sqlite3 "native" date and datetime types
-----------------------------------------------------------
The pysqlite driver includes the sqlite3.PARSE_DECLTYPES and
The pysqlite driver includes the sqlite3.PARSE_DECLTYPES and
sqlite3.PARSE_COLNAMES options, which have the effect of any column
or expression explicitly cast as "date" or "timestamp" will be converted
to a Python date or datetime object. The date and datetime types provided
with the pysqlite dialect are not currently compatible with these options,
since they render the ISO date/datetime including microseconds, which
to a Python date or datetime object. The date and datetime types provided
with the pysqlite dialect are not currently compatible with these options,
since they render the ISO date/datetime including microseconds, which
pysqlite's driver does not. Additionally, SQLAlchemy does not at
this time automatically render the "cast" syntax required for the
this time automatically render the "cast" syntax required for the
freestanding functions "current_timestamp" and "current_date" to return
datetime/date types natively. Unfortunately, pysqlite
datetime/date types natively. Unfortunately, pysqlite
does not provide the standard DBAPI types in ``cursor.description``,
leaving SQLAlchemy with no way to detect these types on the fly
leaving SQLAlchemy with no way to detect these types on the fly
without expensive per-row type checks.
Keeping in mind that pysqlite's parsing option is not recommended,
nor should be necessary, for use with SQLAlchemy, usage of PARSE_DECLTYPES
nor should be necessary, for use with SQLAlchemy, usage of PARSE_DECLTYPES
can be forced if one configures "native_datetime=True" on create_engine()::
engine = create_engine('sqlite://',
engine = create_engine('sqlite://',
connect_args={'detect_types': sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES},
native_datetime=True
)
@@ -97,37 +97,40 @@ 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
in more than one thread. This is originally 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.
Pysqlite does include a now-undocumented flag known as
``check_same_thread`` which will disable this check, however note that pysqlite
connections are still not safe to use in concurrently in multiple threads.
In particular, any statement execution calls would need to be externally
mutexed, as Pysqlite does not provide for thread-safe propagation of error
messages among other things. So while even ``:memory:`` databases can be
shared among threads in modern SQLite, Pysqlite doesn't provide enough
thread-safety to make this usage worth it.
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
same ``:memory:`` database - other threads would access a different
``:memory:`` database.
* When a file-based database is specified, the dialect will use :class:`.NullPool`
* 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.
.. versionchanged:: 0.7
Default selection of :class:`.NullPool` for SQLite file-based databases.
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.
Using a Memory Database in Multiple Threads
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -143,7 +146,7 @@ can be passed to Pysqlite as ``False``::
connect_args={'check_same_thread':False},
poolclass=StaticPool)
Note that using a ``:memory:`` database in multiple threads requires a recent
Note that using a ``:memory:`` database in multiple threads requires a recent
version of SQLite.
Using Temporary Tables with SQLite
@@ -177,8 +180,8 @@ Unicode
The pysqlite driver only returns Python ``unicode`` objects in result sets, never
plain strings, and accommodates ``unicode`` objects within bound parameter
values in all cases. Regardless of the SQLAlchemy string type in use,
string-based result values will by Python ``unicode`` in Python 2.
values in all cases. Regardless of the SQLAlchemy string type in use,
string-based result values will by Python ``unicode`` in Python 2.
The :class:`.Unicode` type should still be used to indicate those columns that
require unicode, however, so that non-``unicode`` values passed inadvertently
will emit a warning. Pysqlite will emit an error if a non-``unicode`` string
@@ -193,7 +196,7 @@ The pysqlite DBAPI driver has a long-standing bug in which transactional
state is not begun until the first DML statement, that is INSERT, UPDATE
or DELETE, is emitted. A SELECT statement will not cause transactional
state to begin. While this mode of usage is fine for typical situations
and has the advantage that the SQLite database file is not prematurely
and has the advantage that the SQLite database file is not prematurely
locked, it breaks serializable transaction isolation, which requires
that the database file be locked upon any SQL being emitted.