<commit_before># sqlite/pysqlite.py
# Copyright (C) 2005-2012 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

"""Support for the SQLite database via pysqlite.

Note that pysqlite is the same driver as the ``sqlite3``
module included with the Python distribution.

Driver
------

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
this explicitly::

    from sqlite3 import dbapi2 as sqlite
    e = create_engine('sqlite+pysqlite:///file.db', module=sqlite)

Full documentation on pysqlite is available at:
`<http://www.initd.org/pub/software/pysqlite/doc/usage-guide.html>`_

Connect Strings
---------------

The file specification for the SQLite database is taken as the "database" portion of
the URL.  Note that the format of a url is::

    driver://user:pass@host/database

This means that the actual filename to be used starts with the characters to the
**right** of the third slash.   So connecting to a relative filepath looks like::

    # relative path
    e = create_engine('sqlite:///path/to/database.db')

An absolute path, which is denoted by starting with a slash, means you need **four**
slashes::

    # absolute path
    e = create_engine('sqlite:////path/to/database.db')

To use a Windows path, regular drive specifications and backslashes can be used.
Double backslashes are probably needed::

    # absolute path on Windows
    e = create_engine('sqlite:///C:\\\\path\\\\to\\\\database.db')

The sqlite ``:memory:`` identifier is the default if no filepath is present.  Specify
``sqlite://`` and nothing else::

    # in-memory database
    e = create_engine('sqlite://')

Compatibility with sqlite3 "native" date and datetime types
-----------------------------------------------------------

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
pysqlite's driver does not.   Additionally, SQLAlchemy does not at
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
does not provide the standard DBAPI types in ``cursor.description``,
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
can be forced if one configures "native_datetime=True" on create_engine()::

    engine = create_engine('sqlite://',
                    connect_args={'detect_types': sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES},
                    native_datetime=True
                    )

With this flag enabled, the DATE and TIMESTAMP types (but note - not the DATETIME
or TIME types...confused yet ?) will not perform any bind parameter or result
processing. Execution of "func.current_date()" will return a string.
"func.current_timestamp()" is registered as returning a DATETIME type in
SQLAlchemy, so this function still receives SQLAlchemy-level result processing.

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.

  .. 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
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

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<commit_msg>some pysqlite doc tweaks<commit_after># sqlite/pysqlite.py
# Copyright (C) 2005-2012 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

"""Support for the SQLite database via pysqlite.

Note that pysqlite is the same driver as the ``sqlite3``
module included with the Python distribution.

Driver
------

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
this explicitly::

    from sqlite3 import dbapi2 as sqlite
    e = create_engine('sqlite+pysqlite:///file.db', module=sqlite)

Full documentation on pysqlite is available at:
`<http://www.initd.org/pub/software/pysqlite/doc/usage-guide.html>`_

Connect Strings
---------------

The file specification for the SQLite database is taken as the "database" portion of
the URL.  Note that the format of a url is::

    driver://user:pass@host/database

This means that the actual filename to be used starts with the characters to the
**right** of the third slash.   So connecting to a relative filepath looks like::

    # relative path
    e = create_engine('sqlite:///path/to/database.db')

An absolute path, which is denoted by starting with a slash, means you need **four**
slashes::

    # absolute path
    e = create_engine('sqlite:////path/to/database.db')

To use a Windows path, regular drive specifications and backslashes can be used.
Double backslashes are probably needed::

    # absolute path on Windows
    e = create_engine('sqlite:///C:\\\\path\\\\to\\\\database.db')

The sqlite ``:memory:`` identifier is the default if no filepath is present.  Specify
``sqlite://`` and nothing else::

    # in-memory database
    e = create_engine('sqlite://')

Compatibility with sqlite3 "native" date and datetime types
-----------------------------------------------------------

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
pysqlite's driver does not.   Additionally, SQLAlchemy does not at
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
does not provide the standard DBAPI types in ``cursor.description``,
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
can be forced if one configures "native_datetime=True" on create_engine()::

    engine = create_engine('sqlite://',
                    connect_args={'detect_types': sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES},
                    native_datetime=True
                    )

With this flag enabled, the DATE and TIMESTAMP types (but note - not the DATETIME
or TIME types...confused yet ?) will not perform any bind parameter or result
processing. Execution of "func.current_date()" will return a string.
"func.current_timestamp()" is registered as returning a DATETIME type in
SQLAlchemy, so this function still receives SQLAlchemy-level result processing.

Threading/Pooling Behavior
---------------------------

Pysqlite's default behavior is to prohibit the usage of a single connection
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
  ``: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.

  .. versionchanged:: 0.7
      Default selection of :class:`.NullPool` for SQLite file-based databases.
      Previous versions select :class:`.SingletonThreadPool` by
      default for all SQLite databases.


Using a Memory Database in Multiple 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
{'fraction_non_alphanumeric': 0.08929544569871545, 'fraction_numerical': 0.00397041650447645, 'mean_word_length': 4.029757243539546, 'pattern_counts': {'":': 0, '<': 7, '<?xml version=': 0, '>': 7, 'https://': 0, 'lorem ipsum': 0, 'www.': 4, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '2355339', 'n_tokens_mistral': 3438, 'n_tokens_neox': 3282, 'n_words': 1618}