608 lines
23 KiB
Python
608 lines
23 KiB
Python
# sqlite/pysqlite.py
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# Copyright (C) 2005-2021 the SQLAlchemy authors and contributors
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# <see AUTHORS file>
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#
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# This module is part of SQLAlchemy and is released under
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# the MIT License: http://www.opensource.org/licenses/mit-license.php
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r"""
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.. dialect:: sqlite+pysqlite
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:name: pysqlite
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:dbapi: sqlite3
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:connectstring: sqlite+pysqlite:///file_path
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:url: http://docs.python.org/library/sqlite3.html
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Note that ``pysqlite`` is the same driver as the ``sqlite3``
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module included with the Python distribution.
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Driver
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------
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The ``sqlite3`` Python DBAPI is standard on all modern Python versions;
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for cPython and Pypy, no additional installation is necessary.
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Connect Strings
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---------------
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The file specification for the SQLite database is taken as the "database"
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portion of the URL. Note that the format of a SQLAlchemy url is::
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driver://user:pass@host/database
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This means that the actual filename to be used starts with the characters to
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the **right** of the third slash. So connecting to a relative filepath
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looks like::
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# relative path
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e = create_engine('sqlite:///path/to/database.db')
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An absolute path, which is denoted by starting with a slash, means you
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need **four** slashes::
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# absolute path
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e = create_engine('sqlite:////path/to/database.db')
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To use a Windows path, regular drive specifications and backslashes can be
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used. Double backslashes are probably needed::
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# absolute path on Windows
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e = create_engine('sqlite:///C:\\path\\to\\database.db')
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The sqlite ``:memory:`` identifier is the default if no filepath is
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present. Specify ``sqlite://`` and nothing else::
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# in-memory database
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e = create_engine('sqlite://')
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.. _pysqlite_uri_connections:
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URI Connections
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^^^^^^^^^^^^^^^
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Modern versions of SQLite support an alternative system of connecting using a
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`driver level URI <https://www.sqlite.org/uri.html>`_, which has the advantage
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that additional driver-level arguments can be passed including options such as
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"read only". The Python sqlite3 driver supports this mode under modern Python
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3 versions. The SQLAlchemy pysqlite driver supports this mode of use by
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specifying "uri=true" in the URL query string. The SQLite-level "URI" is kept
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as the "database" portion of the SQLAlchemy url (that is, following a slash)::
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e = create_engine("sqlite:///file:path/to/database?mode=ro&uri=true")
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.. note:: The "uri=true" parameter must appear in the **query string**
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of the URL. It will not currently work as expected if it is only
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present in the :paramref:`_sa.create_engine.connect_args`
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parameter dictionary.
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The logic reconciles the simultaneous presence of SQLAlchemy's query string and
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SQLite's query string by separating out the parameters that belong to the
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Python sqlite3 driver vs. those that belong to the SQLite URI. This is
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achieved through the use of a fixed list of parameters known to be accepted by
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the Python side of the driver. For example, to include a URL that indicates
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the Python sqlite3 "timeout" and "check_same_thread" parameters, along with the
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SQLite "mode" and "nolock" parameters, they can all be passed together on the
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query string::
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e = create_engine(
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"sqlite:///file:path/to/database?"
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"check_same_thread=true&timeout=10&mode=ro&nolock=1&uri=true"
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)
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Above, the pysqlite / sqlite3 DBAPI would be passed arguments as::
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sqlite3.connect(
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"file:path/to/database?mode=ro&nolock=1",
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check_same_thread=True, timeout=10, uri=True
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)
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Regarding future parameters added to either the Python or native drivers. new
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parameter names added to the SQLite URI scheme should be automatically
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accommodated by this scheme. New parameter names added to the Python driver
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side can be accommodated by specifying them in the
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:paramref:`_sa.create_engine.connect_args` dictionary,
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until dialect support is
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added by SQLAlchemy. For the less likely case that the native SQLite driver
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adds a new parameter name that overlaps with one of the existing, known Python
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driver parameters (such as "timeout" perhaps), SQLAlchemy's dialect would
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require adjustment for the URL scheme to continue to support this.
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As is always the case for all SQLAlchemy dialects, the entire "URL" process
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can be bypassed in :func:`_sa.create_engine` through the use of the
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:paramref:`_sa.create_engine.creator`
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parameter which allows for a custom callable
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that creates a Python sqlite3 driver level connection directly.
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.. versionadded:: 1.3.9
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.. seealso::
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`Uniform Resource Identifiers <https://www.sqlite.org/uri.html>`_ - in
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the SQLite documentation
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.. _pysqlite_regexp:
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Regular Expression Support
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---------------------------
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.. versionadded:: 1.4
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Support for the :meth:`_sql.ColumnOperators.regexp_match` operator is provided
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using Python's re.search_ function. SQLite itself does not include a working
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regular expression operator; instead, it includes a non-implemented placeholder
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operator ``REGEXP`` that calls a user-defined function that must be provided.
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SQLAlchemy's implementation makes use of the pysqlite create_function_ hook
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as follows::
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def regexp(a, b):
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return re.search(a, b) is not None
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sqlite_connection.create_function(
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"regexp", 2, regexp,
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)
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There is currently no support for regular expression flags as a separate
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argument, as these are not supported by SQLite's REGEXP operator, however these
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may be included inline within the regular expression string. See `Python regular expressions`_ for
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details.
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.. seealso::
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`Python regular expressions`_: Documentation for Python's regular expression syntax.
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.. _create_function: https://docs.python.org/3/library/sqlite3.html#sqlite3.Connection.create_function
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.. _re.search: https://docs.python.org/3/library/re.html#re.search
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.. _Python regular expressions: https://docs.python.org/3/library/re.html#re.search
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Compatibility with sqlite3 "native" date and datetime types
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-----------------------------------------------------------
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The pysqlite driver includes the sqlite3.PARSE_DECLTYPES and
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sqlite3.PARSE_COLNAMES options, which have the effect of any column
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or expression explicitly cast as "date" or "timestamp" will be converted
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to a Python date or datetime object. The date and datetime types provided
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with the pysqlite dialect are not currently compatible with these options,
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since they render the ISO date/datetime including microseconds, which
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pysqlite's driver does not. Additionally, SQLAlchemy does not at
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this time automatically render the "cast" syntax required for the
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freestanding functions "current_timestamp" and "current_date" to return
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datetime/date types natively. Unfortunately, pysqlite
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does not provide the standard DBAPI types in ``cursor.description``,
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leaving SQLAlchemy with no way to detect these types on the fly
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without expensive per-row type checks.
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Keeping in mind that pysqlite's parsing option is not recommended,
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nor should be necessary, for use with SQLAlchemy, usage of PARSE_DECLTYPES
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can be forced if one configures "native_datetime=True" on create_engine()::
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engine = create_engine('sqlite://',
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connect_args={'detect_types':
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sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES},
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native_datetime=True
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)
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With this flag enabled, the DATE and TIMESTAMP types (but note - not the
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DATETIME or TIME types...confused yet ?) will not perform any bind parameter
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or result processing. Execution of "func.current_date()" will return a string.
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"func.current_timestamp()" is registered as returning a DATETIME type in
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SQLAlchemy, so this function still receives SQLAlchemy-level result
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processing.
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.. _pysqlite_threading_pooling:
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Threading/Pooling Behavior
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---------------------------
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Pysqlite's default behavior is to prohibit the usage of a single connection
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in more than one thread. This is originally intended to work with older
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versions of SQLite that did not support multithreaded operation under
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various circumstances. In particular, older SQLite versions
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did not allow a ``:memory:`` database to be used in multiple threads
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under any circumstances.
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Pysqlite does include a now-undocumented flag known as
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``check_same_thread`` which will disable this check, however note that
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pysqlite connections are still not safe to use in concurrently in multiple
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threads. In particular, any statement execution calls would need to be
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externally mutexed, as Pysqlite does not provide for thread-safe propagation
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of error messages among other things. So while even ``:memory:`` databases
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can be shared among threads in modern SQLite, Pysqlite doesn't provide enough
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thread-safety to make this usage worth it.
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SQLAlchemy sets up pooling to work with Pysqlite's default behavior:
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* When a ``:memory:`` SQLite database is specified, the dialect by default
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will use :class:`.SingletonThreadPool`. This pool maintains a single
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connection per thread, so that all access to the engine within the current
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thread use the same ``:memory:`` database - other threads would access a
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different ``:memory:`` database.
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* When a file-based database is specified, the dialect will use
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:class:`.NullPool` as the source of connections. This pool closes and
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discards connections which are returned to the pool immediately. SQLite
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file-based connections have extremely low overhead, so pooling is not
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necessary. The scheme also prevents a connection from being used again in
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a different thread and works best with SQLite's coarse-grained file locking.
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Using a Memory Database in Multiple Threads
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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To use a ``:memory:`` database in a multithreaded scenario, the same
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connection object must be shared among threads, since the database exists
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only within the scope of that connection. The
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:class:`.StaticPool` implementation will maintain a single connection
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globally, and the ``check_same_thread`` flag can be passed to Pysqlite
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as ``False``::
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from sqlalchemy.pool import StaticPool
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engine = create_engine('sqlite://',
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connect_args={'check_same_thread':False},
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poolclass=StaticPool)
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Note that using a ``:memory:`` database in multiple threads requires a recent
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version of SQLite.
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Using Temporary Tables with SQLite
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Due to the way SQLite deals with temporary tables, if you wish to use a
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temporary table in a file-based SQLite database across multiple checkouts
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from the connection pool, such as when using an ORM :class:`.Session` where
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the temporary table should continue to remain after :meth:`.Session.commit` or
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:meth:`.Session.rollback` is called, a pool which maintains a single
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connection must be used. Use :class:`.SingletonThreadPool` if the scope is
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only needed within the current thread, or :class:`.StaticPool` is scope is
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needed within multiple threads for this case::
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# maintain the same connection per thread
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from sqlalchemy.pool import SingletonThreadPool
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engine = create_engine('sqlite:///mydb.db',
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poolclass=SingletonThreadPool)
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# maintain the same connection across all threads
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from sqlalchemy.pool import StaticPool
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engine = create_engine('sqlite:///mydb.db',
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poolclass=StaticPool)
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Note that :class:`.SingletonThreadPool` should be configured for the number
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of threads that are to be used; beyond that number, connections will be
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closed out in a non deterministic way.
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Unicode
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-------
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The pysqlite driver only returns Python ``unicode`` objects in result sets,
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never plain strings, and accommodates ``unicode`` objects within bound
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parameter values in all cases. Regardless of the SQLAlchemy string type in
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use, string-based result values will by Python ``unicode`` in Python 2.
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The :class:`.Unicode` type should still be used to indicate those columns that
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require unicode, however, so that non-``unicode`` values passed inadvertently
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will emit a warning. Pysqlite will emit an error if a non-``unicode`` string
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is passed containing non-ASCII characters.
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Dealing with Mixed String / Binary Columns in Python 3
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------------------------------------------------------
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The SQLite database is weakly typed, and as such it is possible when using
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binary values, which in Python 3 are represented as ``b'some string'``, that a
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particular SQLite database can have data values within different rows where
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some of them will be returned as a ``b''`` value by the Pysqlite driver, and
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others will be returned as Python strings, e.g. ``''`` values. This situation
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is not known to occur if the SQLAlchemy :class:`.LargeBinary` datatype is used
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consistently, however if a particular SQLite database has data that was
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inserted using the Pysqlite driver directly, or when using the SQLAlchemy
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:class:`.String` type which was later changed to :class:`.LargeBinary`, the
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table will not be consistently readable because SQLAlchemy's
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:class:`.LargeBinary` datatype does not handle strings so it has no way of
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"encoding" a value that is in string format.
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To deal with a SQLite table that has mixed string / binary data in the
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same column, use a custom type that will check each row individually::
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# note this is Python 3 only
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from sqlalchemy import String
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from sqlalchemy import TypeDecorator
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class MixedBinary(TypeDecorator):
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impl = String
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cache_ok = True
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def process_result_value(self, value, dialect):
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if isinstance(value, str):
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value = bytes(value, 'utf-8')
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elif value is not None:
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value = bytes(value)
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return value
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Then use the above ``MixedBinary`` datatype in the place where
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:class:`.LargeBinary` would normally be used.
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.. _pysqlite_serializable:
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Serializable isolation / Savepoints / Transactional DDL
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-------------------------------------------------------
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In the section :ref:`sqlite_concurrency`, we refer to the pysqlite
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driver's assortment of issues that prevent several features of SQLite
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from working correctly. The pysqlite DBAPI driver has several
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long-standing bugs which impact the correctness of its transactional
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behavior. In its default mode of operation, SQLite features such as
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SERIALIZABLE isolation, transactional DDL, and SAVEPOINT support are
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non-functional, and in order to use these features, workarounds must
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be taken.
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The issue is essentially that the driver attempts to second-guess the user's
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intent, failing to start transactions and sometimes ending them prematurely, in
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an effort to minimize the SQLite databases's file locking behavior, even
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though SQLite itself uses "shared" locks for read-only activities.
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SQLAlchemy chooses to not alter this behavior by default, as it is the
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long-expected behavior of the pysqlite driver; if and when the pysqlite
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driver attempts to repair these issues, that will be more of a driver towards
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defaults for SQLAlchemy.
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The good news is that with a few events, we can implement transactional
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support fully, by disabling pysqlite's feature entirely and emitting BEGIN
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ourselves. This is achieved using two event listeners::
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from sqlalchemy import create_engine, event
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engine = create_engine("sqlite:///myfile.db")
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@event.listens_for(engine, "connect")
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def do_connect(dbapi_connection, connection_record):
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# disable pysqlite's emitting of the BEGIN statement entirely.
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# also stops it from emitting COMMIT before any DDL.
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dbapi_connection.isolation_level = None
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@event.listens_for(engine, "begin")
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def do_begin(conn):
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# emit our own BEGIN
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conn.exec_driver_sql("BEGIN")
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.. warning:: When using the above recipe, it is advised to not use the
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:paramref:`.Connection.execution_options.isolation_level` setting on
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:class:`_engine.Connection` and :func:`_sa.create_engine`
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with the SQLite driver,
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as this function necessarily will also alter the ".isolation_level" setting.
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Above, we intercept a new pysqlite connection and disable any transactional
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integration. Then, at the point at which SQLAlchemy knows that transaction
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scope is to begin, we emit ``"BEGIN"`` ourselves.
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When we take control of ``"BEGIN"``, we can also control directly SQLite's
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locking modes, introduced at
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`BEGIN TRANSACTION <http://sqlite.org/lang_transaction.html>`_,
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by adding the desired locking mode to our ``"BEGIN"``::
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@event.listens_for(engine, "begin")
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def do_begin(conn):
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conn.exec_driver_sql("BEGIN EXCLUSIVE")
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.. seealso::
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`BEGIN TRANSACTION <http://sqlite.org/lang_transaction.html>`_ -
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on the SQLite site
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`sqlite3 SELECT does not BEGIN a transaction <http://bugs.python.org/issue9924>`_ -
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on the Python bug tracker
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`sqlite3 module breaks transactions and potentially corrupts data <http://bugs.python.org/issue10740>`_ -
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on the Python bug tracker
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""" # noqa
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import os
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import re
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from .base import DATE
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from .base import DATETIME
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from .base import SQLiteDialect
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from ... import exc
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from ... import pool
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from ... import types as sqltypes
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from ... import util
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class _SQLite_pysqliteTimeStamp(DATETIME):
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def bind_processor(self, dialect):
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if dialect.native_datetime:
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return None
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else:
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return DATETIME.bind_processor(self, dialect)
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def result_processor(self, dialect, coltype):
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if dialect.native_datetime:
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return None
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else:
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return DATETIME.result_processor(self, dialect, coltype)
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class _SQLite_pysqliteDate(DATE):
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def bind_processor(self, dialect):
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if dialect.native_datetime:
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return None
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else:
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return DATE.bind_processor(self, dialect)
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def result_processor(self, dialect, coltype):
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if dialect.native_datetime:
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return None
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else:
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return DATE.result_processor(self, dialect, coltype)
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class SQLiteDialect_pysqlite(SQLiteDialect):
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default_paramstyle = "qmark"
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supports_statement_cache = True
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colspecs = util.update_copy(
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SQLiteDialect.colspecs,
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{
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sqltypes.Date: _SQLite_pysqliteDate,
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sqltypes.TIMESTAMP: _SQLite_pysqliteTimeStamp,
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},
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)
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if not util.py2k:
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description_encoding = None
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driver = "pysqlite"
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@classmethod
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def dbapi(cls):
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if util.py2k:
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try:
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from pysqlite2 import dbapi2 as sqlite
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except ImportError:
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try:
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from sqlite3 import dbapi2 as sqlite
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except ImportError as e:
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raise e
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else:
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from sqlite3 import dbapi2 as sqlite
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return sqlite
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@classmethod
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def _is_url_file_db(cls, url):
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if (url.database and url.database != ":memory:") and (
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url.query.get("mode", None) != "memory"
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):
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return True
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else:
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return False
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@classmethod
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def get_pool_class(cls, url):
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if cls._is_url_file_db(url):
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return pool.NullPool
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else:
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return pool.SingletonThreadPool
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def _get_server_version_info(self, connection):
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return self.dbapi.sqlite_version_info
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def set_isolation_level(self, connection, level):
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if hasattr(connection, "connection"):
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dbapi_connection = connection.connection
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else:
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dbapi_connection = connection
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if level == "AUTOCOMMIT":
|
|
dbapi_connection.isolation_level = None
|
|
else:
|
|
dbapi_connection.isolation_level = ""
|
|
return super(SQLiteDialect_pysqlite, self).set_isolation_level(
|
|
connection, level
|
|
)
|
|
|
|
def on_connect(self):
|
|
connect = super(SQLiteDialect_pysqlite, self).on_connect()
|
|
|
|
def regexp(a, b):
|
|
if b is None:
|
|
return None
|
|
return re.search(a, b) is not None
|
|
|
|
def set_regexp(connection):
|
|
if hasattr(connection, "connection"):
|
|
dbapi_connection = connection.connection
|
|
else:
|
|
dbapi_connection = connection
|
|
dbapi_connection.create_function(
|
|
"regexp",
|
|
2,
|
|
regexp,
|
|
)
|
|
|
|
fns = [set_regexp]
|
|
|
|
if self.isolation_level is not None:
|
|
|
|
def iso_level(conn):
|
|
self.set_isolation_level(conn, self.isolation_level)
|
|
|
|
fns.append(iso_level)
|
|
|
|
def connect(conn):
|
|
for fn in fns:
|
|
fn(conn)
|
|
|
|
return connect
|
|
|
|
def create_connect_args(self, url):
|
|
if url.username or url.password or url.host or url.port:
|
|
raise exc.ArgumentError(
|
|
"Invalid SQLite URL: %s\n"
|
|
"Valid SQLite URL forms are:\n"
|
|
" sqlite:///:memory: (or, sqlite://)\n"
|
|
" sqlite:///relative/path/to/file.db\n"
|
|
" sqlite:////absolute/path/to/file.db" % (url,)
|
|
)
|
|
|
|
# theoretically, this list can be augmented, at least as far as
|
|
# parameter names accepted by sqlite3/pysqlite, using
|
|
# inspect.getfullargspec(). for the moment this seems like overkill
|
|
# as these parameters don't change very often, and as always,
|
|
# parameters passed to connect_args will always go to the
|
|
# sqlite3/pysqlite driver.
|
|
pysqlite_args = [
|
|
("uri", bool),
|
|
("timeout", float),
|
|
("isolation_level", str),
|
|
("detect_types", int),
|
|
("check_same_thread", bool),
|
|
("cached_statements", int),
|
|
]
|
|
opts = url.query
|
|
pysqlite_opts = {}
|
|
for key, type_ in pysqlite_args:
|
|
util.coerce_kw_type(opts, key, type_, dest=pysqlite_opts)
|
|
|
|
if pysqlite_opts.get("uri", False):
|
|
uri_opts = dict(opts)
|
|
# here, we are actually separating the parameters that go to
|
|
# sqlite3/pysqlite vs. those that go the SQLite URI. What if
|
|
# two names conflict? again, this seems to be not the case right
|
|
# now, and in the case that new names are added to
|
|
# either side which overlap, again the sqlite3/pysqlite parameters
|
|
# can be passed through connect_args instead of in the URL.
|
|
# If SQLite native URIs add a parameter like "timeout" that
|
|
# we already have listed here for the python driver, then we need
|
|
# to adjust for that here.
|
|
for key, type_ in pysqlite_args:
|
|
uri_opts.pop(key, None)
|
|
filename = url.database
|
|
if uri_opts:
|
|
# sorting of keys is for unit test support
|
|
filename += "?" + (
|
|
"&".join(
|
|
"%s=%s" % (key, uri_opts[key])
|
|
for key in sorted(uri_opts)
|
|
)
|
|
)
|
|
else:
|
|
filename = url.database or ":memory:"
|
|
if filename != ":memory:":
|
|
filename = os.path.abspath(filename)
|
|
|
|
return ([filename], pysqlite_opts)
|
|
|
|
def is_disconnect(self, e, connection, cursor):
|
|
return isinstance(
|
|
e, self.dbapi.ProgrammingError
|
|
) and "Cannot operate on a closed database." in str(e)
|
|
|
|
|
|
dialect = SQLiteDialect_pysqlite
|