bflw/venv/lib/python3.11/site-packages/sqlalchemy/dialects/sqlite/pysqlite.py

# sqlite/pysqlite.py
# Copyright (C) 2005-2022 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: https://www.opensource.org/licenses/mit-license.php

r"""
.. dialect:: sqlite+pysqlite
    :name: pysqlite
    :dbapi: sqlite3
    :connectstring: sqlite+pysqlite:///file_path
    :url: https://docs.python.org/library/sqlite3.html

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

Driver
------

The ``sqlite3`` Python DBAPI is standard on all modern Python versions;
for cPython and Pypy, no additional installation is necessary.


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

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

.. _pysqlite_uri_connections:

URI Connections
^^^^^^^^^^^^^^^

Modern versions of SQLite support an alternative system of connecting using a
`driver level URI <https://www.sqlite.org/uri.html>`_, which has the  advantage
that additional driver-level arguments can be passed including options such as
"read only".   The Python sqlite3 driver supports this mode under modern Python
3 versions.   The SQLAlchemy pysqlite driver supports this mode of use by
specifying "uri=true" in the URL query string.  The SQLite-level "URI" is kept
as the "database" portion of the SQLAlchemy url (that is, following a slash)::

    e = create_engine("sqlite:///file:path/to/database?mode=ro&uri=true")

.. note::  The "uri=true" parameter must appear in the **query string**
   of the URL.  It will not currently work as expected if it is only
   present in the :paramref:`_sa.create_engine.connect_args`
   parameter dictionary.

The logic reconciles the simultaneous presence of SQLAlchemy's query string and
SQLite's query string by separating out the parameters that belong to the
Python sqlite3 driver vs. those that belong to the SQLite URI.  This is
achieved through the use of a fixed list of parameters known to be accepted by
the Python side of the driver.  For example, to include a URL that indicates
the Python sqlite3 "timeout" and "check_same_thread" parameters, along with the
SQLite "mode" and "nolock" parameters, they can all be passed together on the
query string::

    e = create_engine(
        "sqlite:///file:path/to/database?"
        "check_same_thread=true&timeout=10&mode=ro&nolock=1&uri=true"
    )

Above, the pysqlite / sqlite3 DBAPI would be passed arguments as::

    sqlite3.connect(
        "file:path/to/database?mode=ro&nolock=1",
        check_same_thread=True, timeout=10, uri=True
    )

Regarding future parameters added to either the Python or native drivers. new
parameter names added to the SQLite URI scheme should be automatically
accommodated by this scheme.  New parameter names added to the Python driver
side can be accommodated by specifying them in the
:paramref:`_sa.create_engine.connect_args` dictionary,
until dialect support is
added by SQLAlchemy.   For the less likely case that the native SQLite driver
adds a new parameter name that overlaps with one of the existing, known Python
driver parameters (such as "timeout" perhaps), SQLAlchemy's dialect would
require adjustment for the URL scheme to continue to support this.

As is always the case for all SQLAlchemy dialects, the entire "URL" process
can be bypassed in :func:`_sa.create_engine` through the use of the
:paramref:`_sa.create_engine.creator`
parameter which allows for a custom callable
that creates a Python sqlite3 driver level connection directly.

.. versionadded:: 1.3.9

.. seealso::

    `Uniform Resource Identifiers <https://www.sqlite.org/uri.html>`_ - in
    the SQLite documentation

.. _pysqlite_regexp:

Regular Expression Support
---------------------------

.. versionadded:: 1.4

Support for the :meth:`_sql.ColumnOperators.regexp_match` operator is provided
using Python's re.search_ function.  SQLite itself does not include a working
regular expression operator; instead, it includes a non-implemented placeholder
operator ``REGEXP`` that calls a user-defined function that must be provided.

SQLAlchemy's implementation makes use of the pysqlite create_function_ hook
as follows::


    def regexp(a, b):
        return re.search(a, b) is not None

    sqlite_connection.create_function(
        "regexp", 2, regexp,
    )

There is currently no support for regular expression flags as a separate
argument, as these are not supported by SQLite's REGEXP operator, however these
may be included inline within the regular expression string.  See `Python regular expressions`_ for
details.

.. seealso::

    `Python regular expressions`_: Documentation for Python's regular expression syntax.

.. _create_function: https://docs.python.org/3/library/sqlite3.html#sqlite3.Connection.create_function

.. _re.search: https://docs.python.org/3/library/re.html#re.search

.. _Python regular expressions: https://docs.python.org/3/library/re.html#re.search



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.

.. _pysqlite_threading_pooling:

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.

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
    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.

Using Temporary Tables with SQLite
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Due to the way SQLite deals with temporary tables, if you wish to use a
temporary table in a file-based SQLite database across multiple checkouts
from the connection pool, such as when using an ORM :class:`.Session` where
the temporary table should continue to remain after :meth:`.Session.commit` or
:meth:`.Session.rollback` is called, a pool which maintains a single
connection must be used.   Use :class:`.SingletonThreadPool` if the scope is
only needed within the current thread, or :class:`.StaticPool` is scope is
needed within multiple threads for this case::

    # maintain the same connection per thread
    from sqlalchemy.pool import SingletonThreadPool
    engine = create_engine('sqlite:///mydb.db',
                        poolclass=SingletonThreadPool)


    # maintain the same connection across all threads
    from sqlalchemy.pool import StaticPool
    engine = create_engine('sqlite:///mydb.db',
                        poolclass=StaticPool)

Note that :class:`.SingletonThreadPool` should be configured for the number
of threads that are to be used; beyond that number, connections will be
closed out in a non deterministic way.

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.
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
is passed containing non-ASCII characters.

Dealing with Mixed String / Binary Columns in Python 3
------------------------------------------------------

The SQLite database is weakly typed, and as such it is possible when using
binary values, which in Python 3 are represented as ``b'some string'``, that a
particular SQLite database can have data values within different rows where
some of them will be returned as a ``b''`` value by the Pysqlite driver, and
others will be returned as Python strings, e.g. ``''`` values.   This situation
is not known to occur if the SQLAlchemy :class:`.LargeBinary` datatype is used
consistently, however if a particular SQLite database has data that was
inserted using the Pysqlite driver directly, or when using the SQLAlchemy
:class:`.String` type which was later changed to :class:`.LargeBinary`, the
table will not be consistently readable because SQLAlchemy's
:class:`.LargeBinary` datatype does not handle strings so it has no way of
"encoding" a value that is in string format.

To deal with a SQLite table that has mixed string / binary data in the
same column, use a custom type that will check each row individually::

    # note this is Python 3 only

    from sqlalchemy import String
    from sqlalchemy import TypeDecorator

    class MixedBinary(TypeDecorator):
        impl = String
        cache_ok = True

        def process_result_value(self, value, dialect):
            if isinstance(value, str):
                value = bytes(value, 'utf-8')
            elif value is not None:
                value = bytes(value)

            return value

Then use the above ``MixedBinary`` datatype in the place where
:class:`.LargeBinary` would normally be used.

.. _pysqlite_serializable:

Serializable isolation / Savepoints / Transactional DDL
-------------------------------------------------------

In the section :ref:`sqlite_concurrency`, we refer to the pysqlite
driver's assortment of issues that prevent several features of SQLite
from working correctly.  The pysqlite DBAPI driver has several
long-standing bugs which impact the correctness of its transactional
behavior.   In its default mode of operation, SQLite features such as
SERIALIZABLE isolation, transactional DDL, and SAVEPOINT support are
non-functional, and in order to use these features, workarounds must
be taken.

The issue is essentially that the driver attempts to second-guess the user's
intent, failing to start transactions and sometimes ending them prematurely, in
an effort to minimize the SQLite databases's file locking behavior, even
though SQLite itself uses "shared" locks for read-only activities.

SQLAlchemy chooses to not alter this behavior by default, as it is the
long-expected behavior of the pysqlite driver; if and when the pysqlite
driver attempts to repair these issues, that will be more of a driver towards
defaults for SQLAlchemy.

The good news is that with a few events, we can implement transactional
support fully, by disabling pysqlite's feature entirely and emitting BEGIN
ourselves. This is achieved using two event listeners::

    from sqlalchemy import create_engine, event

    engine = create_engine("sqlite:///myfile.db")

    @event.listens_for(engine, "connect")
    def do_connect(dbapi_connection, connection_record):
        # disable pysqlite's emitting of the BEGIN statement entirely.
        # also stops it from emitting COMMIT before any DDL.
        dbapi_connection.isolation_level = None

    @event.listens_for(engine, "begin")
    def do_begin(conn):
        # emit our own BEGIN
        conn.exec_driver_sql("BEGIN")

.. warning:: When using the above recipe, it is advised to not use the
   :paramref:`.Connection.execution_options.isolation_level` setting on
   :class:`_engine.Connection` and :func:`_sa.create_engine`
   with the SQLite driver,
   as this function necessarily will also alter the ".isolation_level" setting.


Above, we intercept a new pysqlite connection and disable any transactional
integration.   Then, at the point at which SQLAlchemy knows that transaction
scope is to begin, we emit ``"BEGIN"`` ourselves.

When we take control of ``"BEGIN"``, we can also control directly SQLite's
locking modes, introduced at
`BEGIN TRANSACTION <https://sqlite.org/lang_transaction.html>`_,
by adding the desired locking mode to our ``"BEGIN"``::

    @event.listens_for(engine, "begin")
    def do_begin(conn):
        conn.exec_driver_sql("BEGIN EXCLUSIVE")

.. seealso::

    `BEGIN TRANSACTION <https://sqlite.org/lang_transaction.html>`_ -
    on the SQLite site

    `sqlite3 SELECT does not BEGIN a transaction <https://bugs.python.org/issue9924>`_ -
    on the Python bug tracker

    `sqlite3 module breaks transactions and potentially corrupts data <https://bugs.python.org/issue10740>`_ -
    on the Python bug tracker

.. _pysqlite_udfs:

User-Defined Functions
----------------------

pysqlite supports a `create_function() <https://docs.python.org/3/library/sqlite3.html#sqlite3.Connection.create_function>`_
method that allows us to create our own user-defined functions (UDFs) in Python and use them directly in SQLite queries.
These functions are registered with a specific DBAPI Connection.

SQLAlchemy uses connection pooling with file-based SQLite databases, so we need to ensure that the UDF is attached to the
connection when it is created. That is accomplished with an event listener::

    from sqlalchemy import create_engine
    from sqlalchemy import event
    from sqlalchemy import text


    def udf():
        return "udf-ok"


    engine = create_engine("sqlite:///./db_file")


    @event.listens_for(engine, "connect")
    def connect(conn, rec):
        conn.create_function("udf", 0, udf)


    for i in range(5):
        with engine.connect() as conn:
            print(conn.scalar(text("SELECT UDF()")))


"""  # noqa

import os
import re

from .base import DATE
from .base import DATETIME
from .base import SQLiteDialect
from ... import exc
from ... import pool
from ... import types as sqltypes
from ... import util


class _SQLite_pysqliteTimeStamp(DATETIME):
    def bind_processor(self, dialect):
        if dialect.native_datetime:
            return None
        else:
            return DATETIME.bind_processor(self, dialect)

    def result_processor(self, dialect, coltype):
        if dialect.native_datetime:
            return None
        else:
            return DATETIME.result_processor(self, dialect, coltype)


class _SQLite_pysqliteDate(DATE):
    def bind_processor(self, dialect):
        if dialect.native_datetime:
            return None
        else:
            return DATE.bind_processor(self, dialect)

    def result_processor(self, dialect, coltype):
        if dialect.native_datetime:
            return None
        else:
            return DATE.result_processor(self, dialect, coltype)


class SQLiteDialect_pysqlite(SQLiteDialect):
    default_paramstyle = "qmark"
    supports_statement_cache = True

    colspecs = util.update_copy(
        SQLiteDialect.colspecs,
        {
            sqltypes.Date: _SQLite_pysqliteDate,
            sqltypes.TIMESTAMP: _SQLite_pysqliteTimeStamp,
        },
    )

    if not util.py2k:
        description_encoding = None

    driver = "pysqlite"

    @classmethod
    def dbapi(cls):
        if util.py2k:
            try:
                from pysqlite2 import dbapi2 as sqlite
            except ImportError:
                try:
                    from sqlite3 import dbapi2 as sqlite
                except ImportError as e:
                    raise e
        else:
            from sqlite3 import dbapi2 as sqlite
        return sqlite

    @classmethod
    def _is_url_file_db(cls, url):
        if (url.database and url.database != ":memory:") and (
            url.query.get("mode", None) != "memory"
        ):
            return True
        else:
            return False

    @classmethod
    def get_pool_class(cls, url):
        if cls._is_url_file_db(url):
            return pool.NullPool
        else:
            return pool.SingletonThreadPool

    def _get_server_version_info(self, connection):
        return self.dbapi.sqlite_version_info

    _isolation_lookup = SQLiteDialect._isolation_lookup.union(
        {
            "AUTOCOMMIT": None,
        }
    )

    def set_isolation_level(self, connection, level):
        if hasattr(connection, "dbapi_connection"):
            dbapi_connection = connection.dbapi_connection
        else:
            dbapi_connection = connection

        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, "dbapi_connection"):
                dbapi_connection = connection.dbapi_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