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📁 ..	-	2026-03-21 15:45
📄 __init__.py # sqlite/__init__.py # Copyright (C) 2005-2021 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 from . import base # noqa from . import pysqlcipher # noqa from . import pysqlite # noqa from .base import BLOB from .base import BOOLEAN from .base import CHAR from .base import DATE from .base import DATETIME from .base import DECIMAL from .base import FLOAT from .base import INTEGER from .base import JSON from .base import NUMERIC from .base import REAL from .base import SMALLINT from .base import TEXT from .base import TIME from .base import TIMESTAMP from .base import VARCHAR # default dialect base.dialect = dialect = pysqlite.dialect __all__ = ( "BLOB", "BOOLEAN", "CHAR", "DATE", "DATETIME", "DECIMAL", "FLOAT", "INTEGER", "JSON", "NUMERIC", "SMALLINT", "TEXT", "TIME", "TIMESTAMP", "VARCHAR", "REAL", "dialect", )	1.02 KB	2026-01-20 12:58
📁 __pycache__	-	2026-03-21 15:45
📄 base.py # sqlite/base.py # Copyright (C) 2005-2021 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 r""" .. dialect:: sqlite :name: SQLite .. _sqlite_datetime: Date and Time Types ------------------- SQLite does not have built-in DATE, TIME, or DATETIME types, and pysqlite does not provide out of the box functionality for translating values between Python `datetime` objects and a SQLite-supported format. SQLAlchemy's own :class:`~sqlalchemy.types.DateTime` and related types provide date formatting and parsing functionality when SQLite is used. The implementation classes are :class:`_sqlite.DATETIME`, :class:`_sqlite.DATE` and :class:`_sqlite.TIME`. These types represent dates and times as ISO formatted strings, which also nicely support ordering. There's no reliance on typical "libc" internals for these functions so historical dates are fully supported. Ensuring Text affinity ^^^^^^^^^^^^^^^^^^^^^^ The DDL rendered for these types is the standard ``DATE``, ``TIME`` and ``DATETIME`` indicators. However, custom storage formats can also be applied to these types. When the storage format is detected as containing no alpha characters, the DDL for these types is rendered as ``DATE_CHAR``, ``TIME_CHAR``, and ``DATETIME_CHAR``, so that the column continues to have textual affinity. .. seealso:: `Type Affinity <http://www.sqlite.org/datatype3.html#affinity>`_ - in the SQLite documentation .. _sqlite_autoincrement: SQLite Auto Incrementing Behavior ---------------------------------- Background on SQLite's autoincrement is at: http://sqlite.org/autoinc.html Key concepts: * SQLite has an implicit "auto increment" feature that takes place for any non-composite primary-key column that is specifically created using "INTEGER PRIMARY KEY" for the type + primary key. * SQLite also has an explicit "AUTOINCREMENT" keyword, that is not equivalent to the implicit autoincrement feature; this keyword is not recommended for general use. SQLAlchemy does not render this keyword unless a special SQLite-specific directive is used (see below). However, it still requires that the column's type is named "INTEGER". Using the AUTOINCREMENT Keyword ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ To specifically render the AUTOINCREMENT keyword on the primary key column when rendering DDL, add the flag ``sqlite_autoincrement=True`` to the Table construct:: Table('sometable', metadata, Column('id', Integer, primary_key=True), sqlite_autoincrement=True) Allowing autoincrement behavior SQLAlchemy types other than Integer/INTEGER ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ SQLite's typing model is based on naming conventions. Among other things, this means that any type name which contains the substring ``"INT"`` will be determined to be of "integer affinity". A type named ``"BIGINT"``, ``"SPECIAL_INT"`` or even ``"XYZINTQPR"``, will be considered by SQLite to be of "integer" affinity. However, the SQLite autoincrement feature, whether implicitly or explicitly enabled, requires that the name of the column's type is exactly the string "INTEGER". Therefore, if an application uses a type like :class:`.BigInteger` for a primary key, on SQLite this type will need to be rendered as the name ``"INTEGER"`` when emitting the initial ``CREATE TABLE`` statement in order for the autoincrement behavior to be available. One approach to achieve this is to use :class:`.Integer` on SQLite only using :meth:`.TypeEngine.with_variant`:: table = Table( "my_table", metadata, Column("id", BigInteger().with_variant(Integer, "sqlite"), primary_key=True) ) Another is to use a subclass of :class:`.BigInteger` that overrides its DDL name to be ``INTEGER`` when compiled against SQLite:: from sqlalchemy import BigInteger from sqlalchemy.ext.compiler import compiles class SLBigInteger(BigInteger): pass @compiles(SLBigInteger, 'sqlite') def bi_c(element, compiler, kw): return "INTEGER" @compiles(SLBigInteger) def bi_c(element, compiler, kw): return compiler.visit_BIGINT(element, *kw) table = Table( "my_table", metadata, Column("id", SLBigInteger(), primary_key=True) ) .. seealso:: :meth:`.TypeEngine.with_variant` :ref:`sqlalchemy.ext.compiler_toplevel` `Datatypes In SQLite Version 3 <http://sqlite.org/datatype3.html>`_ .. _sqlite_concurrency: Database Locking Behavior / Concurrency --------------------------------------- SQLite is not designed for a high level of write concurrency. The database itself, being a file, is locked completely during write operations within transactions, meaning exactly one "connection" (in reality a file handle) has exclusive access to the database during this period - all other "connections" will be blocked during this time. The Python DBAPI specification also calls for a connection model that is always in a transaction; there is no ``connection.begin()`` method, only ``connection.commit()`` and ``connection.rollback()``, upon which a new transaction is to be begun immediately. This may seem to imply that the SQLite driver would in theory allow only a single filehandle on a particular database file at any time; however, there are several factors both within SQLite itself as well as within the pysqlite driver which loosen this restriction significantly. However, no matter what locking modes are used, SQLite will still always lock the database file once a transaction is started and DML (e.g. INSERT, UPDATE, DELETE) has at least been emitted, and this will block other transactions at least at the point that they also attempt to emit DML. By default, the length of time on this block is very short before it times out with an error. This behavior becomes more critical when used in conjunction with the SQLAlchemy ORM. SQLAlchemy's :class:`.Session` object by default runs within a transaction, and with its autoflush model, may emit DML preceding any SELECT statement. This may lead to a SQLite database that locks more quickly than is expected. The locking mode of SQLite and the pysqlite driver can be manipulated to some degree, however it should be noted that achieving a high degree of write-concurrency with SQLite is a losing battle. For more information on SQLite's lack of write concurrency by design, please see `Situations Where Another RDBMS May Work Better - High Concurrency <http://www.sqlite.org/whentouse.html>`_ near the bottom of the page. The following subsections introduce areas that are impacted by SQLite's file-based architecture and additionally will usually require workarounds to work when using the pysqlite driver. .. _sqlite_isolation_level: Transaction Isolation Level / Autocommit ---------------------------------------- SQLite supports "transaction isolation" in a non-standard way, along two axes. One is that of the `PRAGMA read_uncommitted <http://www.sqlite.org/pragma.html#pragma_read_uncommitted>`_ instruction. This setting can essentially switch SQLite between its default mode of ``SERIALIZABLE`` isolation, and a "dirty read" isolation mode normally referred to as ``READ UNCOMMITTED``. SQLAlchemy ties into this PRAGMA statement using the :paramref:`_sa.create_engine.isolation_level` parameter of :func:`_sa.create_engine`. Valid values for this parameter when used with SQLite are ``"SERIALIZABLE"`` and ``"READ UNCOMMITTED"`` corresponding to a value of 0 and 1, respectively. SQLite defaults to ``SERIALIZABLE``, however its behavior is impacted by the pysqlite driver's default behavior. When using the pysqlite driver, the ``"AUTOCOMMIT"`` isolation level is also available, which will alter the pysqlite connection using the ``.isolation_level`` attribute on the DBAPI connection and set it to None for the duration of the setting. .. versionadded:: 1.3.16 added support for SQLite AUTOCOMMIT isolation level when using the pysqlite / sqlite3 SQLite driver. The other axis along which SQLite's transactional locking is impacted is via the nature of the ``BEGIN`` statement used. The three varieties are "deferred", "immediate", and "exclusive", as described at `BEGIN TRANSACTION <http://sqlite.org/lang_transaction.html>`_. A straight ``BEGIN`` statement uses the "deferred" mode, where the database file is not locked until the first read or write operation, and read access remains open to other transactions until the first write operation. But again, it is critical to note that the pysqlite driver interferes with this behavior by not even emitting BEGIN* until the first write operation. .. warning:: SQLite's transactional scope is impacted by unresolved issues in the pysqlite driver, which defers BEGIN statements to a greater degree than is often feasible. See the section :ref:`pysqlite_serializable` for techniques to work around this behavior. .. seealso:: :ref:`dbapi_autocommit` SAVEPOINT Support ---------------------------- SQLite supports SAVEPOINTs, which only function once a transaction is begun. SQLAlchemy's SAVEPOINT support is available using the :meth:`_engine.Connection.begin_nested` method at the Core level, and :meth:`.Session.begin_nested` at the ORM level. However, SAVEPOINTs won't work at all with pysqlite unless workarounds are taken. .. warning:: SQLite's SAVEPOINT feature is impacted by unresolved issues in the pysqlite driver, which defers BEGIN statements to a greater degree than is often feasible. See the section :ref:`pysqlite_serializable` for techniques to work around this behavior. Transactional DDL ---------------------------- The SQLite database supports transactional :term:`DDL` as well. In this case, the pysqlite driver is not only failing to start transactions, it also is ending any existing transaction when DDL is detected, so again, workarounds are required. .. warning:: SQLite's transactional DDL is impacted by unresolved issues in the pysqlite driver, which fails to emit BEGIN and additionally forces a COMMIT to cancel any transaction when DDL is encountered. See the section :ref:`pysqlite_serializable` for techniques to work around this behavior. .. _sqlite_foreign_keys: Foreign Key Support ------------------- SQLite supports FOREIGN KEY syntax when emitting CREATE statements for tables, however by default these constraints have no effect on the operation of the table. Constraint checking on SQLite has three prerequisites: * At least version 3.6.19 of SQLite must be in use * The SQLite library must be compiled without the SQLITE_OMIT_FOREIGN_KEY or SQLITE_OMIT_TRIGGER symbols enabled. * The ``PRAGMA foreign_keys = ON`` statement must be emitted on all connections before use. SQLAlchemy allows for the ``PRAGMA`` statement to be emitted automatically for new connections through the usage of events:: from sqlalchemy.engine import Engine from sqlalchemy import event @event.listens_for(Engine, "connect") def set_sqlite_pragma(dbapi_connection, connection_record): cursor = dbapi_connection.cursor() cursor.execute("PRAGMA foreign_keys=ON") cursor.close() .. warning:: When SQLite foreign keys are enabled, it is not possible to emit CREATE or DROP statements for tables that contain mutually-dependent foreign key constraints; to emit the DDL for these tables requires that ALTER TABLE be used to create or drop these constraints separately, for which SQLite has no support. .. seealso:: `SQLite Foreign Key Support <http://www.sqlite.org/foreignkeys.html>`_ - on the SQLite web site. :ref:`event_toplevel` - SQLAlchemy event API. :ref:`use_alter` - more information on SQLAlchemy's facilities for handling mutually-dependent foreign key constraints. .. _sqlite_on_conflict_ddl: ON CONFLICT support for constraints ----------------------------------- SQLite supports a non-standard clause known as ON CONFLICT which can be applied to primary key, unique, check, and not null constraints. In DDL, it is rendered either within the "CONSTRAINT" clause or within the column definition itself depending on the location of the target constraint. To render this clause within DDL, the extension parameter ``sqlite_on_conflict`` can be specified with a string conflict resolution algorithm within the :class:`.PrimaryKeyConstraint`, :class:`.UniqueConstraint`, :class:`.CheckConstraint` objects. Within the :class:`_schema.Column` object, there are individual parameters ``sqlite_on_conflict_not_null``, ``sqlite_on_conflict_primary_key``, ``sqlite_on_conflict_unique`` which each correspond to the three types of relevant constraint types that can be indicated from a :class:`_schema.Column` object. .. seealso:: `ON CONFLICT <https://www.sqlite.org/lang_conflict.html>`_ - in the SQLite documentation .. versionadded:: 1.3 The ``sqlite_on_conflict`` parameters accept a string argument which is just the resolution name to be chosen, which on SQLite can be one of ROLLBACK, ABORT, FAIL, IGNORE, and REPLACE. For example, to add a UNIQUE constraint that specifies the IGNORE algorithm:: some_table = Table( 'some_table', metadata, Column('id', Integer, primary_key=True), Column('data', Integer), UniqueConstraint('id', 'data', sqlite_on_conflict='IGNORE') ) The above renders CREATE TABLE DDL as:: CREATE TABLE some_table ( id INTEGER NOT NULL, data INTEGER, PRIMARY KEY (id), UNIQUE (id, data) ON CONFLICT IGNORE ) When using the :paramref:`_schema.Column.unique` flag to add a UNIQUE constraint to a single column, the ``sqlite_on_conflict_unique`` parameter can be added to the :class:`_schema.Column` as well, which will be added to the UNIQUE constraint in the DDL:: some_table = Table( 'some_table', metadata, Column('id', Integer, primary_key=True), Column('data', Integer, unique=True, sqlite_on_conflict_unique='IGNORE') ) rendering:: CREATE TABLE some_table ( id INTEGER NOT NULL, data INTEGER, PRIMARY KEY (id), UNIQUE (data) ON CONFLICT IGNORE ) To apply the FAIL algorithm for a NOT NULL constraint, ``sqlite_on_conflict_not_null`` is used:: some_table = Table( 'some_table', metadata, Column('id', Integer, primary_key=True), Column('data', Integer, nullable=False, sqlite_on_conflict_not_null='FAIL') ) this renders the column inline ON CONFLICT phrase:: CREATE TABLE some_table ( id INTEGER NOT NULL, data INTEGER NOT NULL ON CONFLICT FAIL, PRIMARY KEY (id) ) Similarly, for an inline primary key, use ``sqlite_on_conflict_primary_key``:: some_table = Table( 'some_table', metadata, Column('id', Integer, primary_key=True, sqlite_on_conflict_primary_key='FAIL') ) SQLAlchemy renders the PRIMARY KEY constraint separately, so the conflict resolution algorithm is applied to the constraint itself:: CREATE TABLE some_table ( id INTEGER NOT NULL, PRIMARY KEY (id) ON CONFLICT FAIL ) .. _sqlite_type_reflection: Type Reflection --------------- SQLite types are unlike those of most other database backends, in that the string name of the type usually does not correspond to a "type" in a one-to-one fashion. Instead, SQLite links per-column typing behavior to one of five so-called "type affinities" based on a string matching pattern for the type. SQLAlchemy's reflection process, when inspecting types, uses a simple lookup table to link the keywords returned to provided SQLAlchemy types. This lookup table is present within the SQLite dialect as it is for all other dialects. However, the SQLite dialect has a different "fallback" routine for when a particular type name is not located in the lookup map; it instead implements the SQLite "type affinity" scheme located at http://www.sqlite.org/datatype3.html section 2.1. The provided typemap will make direct associations from an exact string name match for the following types: :class:`_types.BIGINT`, :class:`_types.BLOB`, :class:`_types.BOOLEAN`, :class:`_types.BOOLEAN`, :class:`_types.CHAR`, :class:`_types.DATE`, :class:`_types.DATETIME`, :class:`_types.FLOAT`, :class:`_types.DECIMAL`, :class:`_types.FLOAT`, :class:`_types.INTEGER`, :class:`_types.INTEGER`, :class:`_types.NUMERIC`, :class:`_types.REAL`, :class:`_types.SMALLINT`, :class:`_types.TEXT`, :class:`_types.TIME`, :class:`_types.TIMESTAMP`, :class:`_types.VARCHAR`, :class:`_types.NVARCHAR`, :class:`_types.NCHAR` When a type name does not match one of the above types, the "type affinity" lookup is used instead: * :class:`_types.INTEGER` is returned if the type name includes the string ``INT`` * :class:`_types.TEXT` is returned if the type name includes the string ``CHAR``, ``CLOB`` or ``TEXT`` * :class:`_types.NullType` is returned if the type name includes the string ``BLOB`` * :class:`_types.REAL` is returned if the type name includes the string ``REAL``, ``FLOA`` or ``DOUB``. * Otherwise, the :class:`_types.NUMERIC` type is used. .. versionadded:: 0.9.3 Support for SQLite type affinity rules when reflecting columns. .. _sqlite_partial_index: Partial Indexes --------------- A partial index, e.g. one which uses a WHERE clause, can be specified with the DDL system using the argument ``sqlite_where``:: tbl = Table('testtbl', m, Column('data', Integer)) idx = Index('test_idx1', tbl.c.data, sqlite_where=and_(tbl.c.data > 5, tbl.c.data < 10)) The index will be rendered at create time as:: CREATE INDEX test_idx1 ON testtbl (data) WHERE data > 5 AND data < 10 .. versionadded:: 0.9.9 .. _sqlite_dotted_column_names: Dotted Column Names ------------------- Using table or column names that explicitly have periods in them is not recommended. While this is generally a bad idea for relational databases in general, as the dot is a syntactically significant character, the SQLite driver up until version 3.10.0 of SQLite has a bug which requires that SQLAlchemy filter out these dots in result sets. .. versionchanged:: 1.1 The following SQLite issue has been resolved as of version 3.10.0 of SQLite. SQLAlchemy as of 1.1 automatically disables its internal workarounds based on detection of this version. The bug, entirely outside of SQLAlchemy, can be illustrated thusly:: import sqlite3 assert sqlite3.sqlite_version_info < (3, 10, 0), "bug is fixed in this version" conn = sqlite3.connect(":memory:") cursor = conn.cursor() cursor.execute("create table x (a integer, b integer)") cursor.execute("insert into x (a, b) values (1, 1)") cursor.execute("insert into x (a, b) values (2, 2)") cursor.execute("select x.a, x.b from x") assert [c[0] for c in cursor.description] == ['a', 'b'] cursor.execute(''' select x.a, x.b from x where a=1 union select x.a, x.b from x where a=2 ''') assert [c[0] for c in cursor.description] == ['a', 'b'], \ [c[0] for c in cursor.description] The second assertion fails:: Traceback (most recent call last): File "test.py", line 19, in <module> [c[0] for c in cursor.description] AssertionError: ['x.a', 'x.b'] Where above, the driver incorrectly reports the names of the columns including the name of the table, which is entirely inconsistent vs. when the UNION is not present. SQLAlchemy relies upon column names being predictable in how they match to the original statement, so the SQLAlchemy dialect has no choice but to filter these out:: from sqlalchemy import create_engine eng = create_engine("sqlite://") conn = eng.connect() conn.execute("create table x (a integer, b integer)") conn.execute("insert into x (a, b) values (1, 1)") conn.execute("insert into x (a, b) values (2, 2)") result = conn.execute("select x.a, x.b from x") assert result.keys() == ["a", "b"] result = conn.execute(''' select x.a, x.b from x where a=1 union select x.a, x.b from x where a=2 ''') assert result.keys() == ["a", "b"] Note that above, even though SQLAlchemy filters out the dots, both names are still addressable:: >>> row = result.first() >>> row["a"] 1 >>> row["x.a"] 1 >>> row["b"] 1 >>> row["x.b"] 1 Therefore, the workaround applied by SQLAlchemy only impacts :meth:`_engine.ResultProxy.keys` and :meth:`.RowProxy.keys()` in the public API. In the very specific case where an application is forced to use column names that contain dots, and the functionality of :meth:`_engine.ResultProxy.keys` and :meth:`.RowProxy.keys()` is required to return these dotted names unmodified, the ``sqlite_raw_colnames`` execution option may be provided, either on a per-:class:`_engine.Connection` basis:: result = conn.execution_options(sqlite_raw_colnames=True).execute(''' select x.a, x.b from x where a=1 union select x.a, x.b from x where a=2 ''') assert result.keys() == ["x.a", "x.b"] or on a per-:class:`_engine.Engine` basis:: engine = create_engine("sqlite://", execution_options={"sqlite_raw_colnames": True}) When using the per-:class:`_engine.Engine` execution option, note that Core and ORM queries that use UNION may not function properly. SQLite-specific table options ----------------------------- One option for CREATE TABLE is supported directly by the SQLite dialect in conjunction with the :class:`_schema.Table` construct: * ``WITHOUT ROWID``:: Table("some_table", metadata, ..., sqlite_with_rowid=False) .. seealso:: `SQLite CREATE TABLE options <https://www.sqlite.org/lang_createtable.html>`_ """ # noqa import datetime import numbers import re from .json import JSON from .json import JSONIndexType from .json import JSONPathType from ... import exc from ... import processors from ... import schema as sa_schema from ... import sql from ... import types as sqltypes from ... import util from ...engine import default from ...engine import reflection from ...sql import ColumnElement from ...sql import compiler from ...sql import schema from ...types import BLOB # noqa from ...types import BOOLEAN # noqa from ...types import CHAR # noqa from ...types import DECIMAL # noqa from ...types import FLOAT # noqa from ...types import INTEGER # noqa from ...types import NUMERIC # noqa from ...types import REAL # noqa from ...types import SMALLINT # noqa from ...types import TEXT # noqa from ...types import TIMESTAMP # noqa from ...types import VARCHAR # noqa class _SQliteJson(JSON): def result_processor(self, dialect, coltype): default_processor = super(_SQliteJson, self).result_processor( dialect, coltype ) def process(value): try: return default_processor(value) except TypeError: if isinstance(value, numbers.Number): return value else: raise return process class _DateTimeMixin(object): _reg = None _storage_format = None def __init__(self, storage_format=None, regexp=None, kw): super(_DateTimeMixin, self).__init__(kw) if regexp is not None: self._reg = re.compile(regexp) if storage_format is not None: self._storage_format = storage_format @property def format_is_text_affinity(self): """return True if the storage format will automatically imply a TEXT affinity. If the storage format contains no non-numeric characters, it will imply a NUMERIC storage format on SQLite; in this case, the type will generate its DDL as DATE_CHAR, DATETIME_CHAR, TIME_CHAR. .. versionadded:: 1.0.0 """ spec = self._storage_format % { "year": 0, "month": 0, "day": 0, "hour": 0, "minute": 0, "second": 0, "microsecond": 0, } return bool(re.search(r"[^0-9]", spec)) def adapt(self, cls, kw): if issubclass(cls, _DateTimeMixin): if self._storage_format: kw["storage_format"] = self._storage_format if self._reg: kw["regexp"] = self._reg return super(_DateTimeMixin, self).adapt(cls, kw) def literal_processor(self, dialect): bp = self.bind_processor(dialect) def process(value): return "'%s'" % bp(value) return process class DATETIME(_DateTimeMixin, sqltypes.DateTime): r"""Represent a Python datetime object in SQLite using a string. The default string storage format is:: "%(year)04d-%(month)02d-%(day)02d %(hour)02d:%(minute)02d:%(second)02d.%(microsecond)06d" e.g.:: 2011-03-15 12:05:57.10558 The storage format can be customized to some degree using the ``storage_format`` and ``regexp`` parameters, such as:: import re from sqlalchemy.dialects.sqlite import DATETIME dt = DATETIME(storage_format="%(year)04d/%(month)02d/%(day)02d " "%(hour)02d:%(minute)02d:%(second)02d", regexp=r"(\d+)/(\d+)/(\d+) (\d+)-(\d+)-(\d+)" ) :param storage_format: format string which will be applied to the dict with keys year, month, day, hour, minute, second, and microsecond. :param regexp: regular expression which will be applied to incoming result rows. If the regexp contains named groups, the resulting match dict is applied to the Python datetime() constructor as keyword arguments. Otherwise, if positional groups are used, the datetime() constructor is called with positional arguments via ``map(int, match_obj.groups(0))``. """ # noqa _storage_format = ( "%(year)04d-%(month)02d-%(day)02d " "%(hour)02d:%(minute)02d:%(second)02d.%(microsecond)06d" ) def __init__(self, args, *kwargs): truncate_microseconds = kwargs.pop("truncate_microseconds", False) super(DATETIME, self).__init__(args, *kwargs) if truncate_microseconds: assert "storage_format" not in kwargs, ( "You can specify only " "one of truncate_microseconds or storage_format." ) assert "regexp" not in kwargs, ( "You can specify only one of " "truncate_microseconds or regexp." ) self._storage_format = ( "%(year)04d-%(month)02d-%(day)02d " "%(hour)02d:%(minute)02d:%(second)02d" ) def bind_processor(self, dialect): datetime_datetime = datetime.datetime datetime_date = datetime.date format_ = self._storage_format def process(value): if value is None: return None elif isinstance(value, datetime_datetime): return format_ % { "year": value.year, "month": value.month, "day": value.day, "hour": value.hour, "minute": value.minute, "second": value.second, "microsecond": value.microsecond, } elif isinstance(value, datetime_date): return format_ % { "year": value.year, "month": value.month, "day": value.day, "hour": 0, "minute": 0, "second": 0, "microsecond": 0, } else: raise TypeError( "SQLite DateTime type only accepts Python " "datetime and date objects as input." ) return process def result_processor(self, dialect, coltype): if self._reg: return processors.str_to_datetime_processor_factory( self._reg, datetime.datetime ) else: return processors.str_to_datetime class DATE(_DateTimeMixin, sqltypes.Date): r"""Represent a Python date object in SQLite using a string. The default string storage format is:: "%(year)04d-%(month)02d-%(day)02d" e.g.:: 2011-03-15 The storage format can be customized to some degree using the ``storage_format`` and ``regexp`` parameters, such as:: import re from sqlalchemy.dialects.sqlite import DATE d = DATE( storage_format="%(month)02d/%(day)02d/%(year)04d", regexp=re.compile("(?P<month>\d+)/(?P<day>\d+)/(?P<year>\d+)") ) :param storage_format: format string which will be applied to the dict with keys year, month, and day. :param regexp: regular expression which will be applied to incoming result rows. If the regexp contains named groups, the resulting match dict is applied to the Python date() constructor as keyword arguments. Otherwise, if positional groups are used, the date() constructor is called with positional arguments via ``map(int, match_obj.groups(0))``. """ _storage_format = "%(year)04d-%(month)02d-%(day)02d" def bind_processor(self, dialect): datetime_date = datetime.date format_ = self._storage_format def process(value): if value is None: return None elif isinstance(value, datetime_date): return format_ % { "year": value.year, "month": value.month, "day": value.day, } else: raise TypeError( "SQLite Date type only accepts Python " "date objects as input." ) return process def result_processor(self, dialect, coltype): if self._reg: return processors.str_to_datetime_processor_factory( self._reg, datetime.date ) else: return processors.str_to_date class TIME(_DateTimeMixin, sqltypes.Time): r"""Represent a Python time object in SQLite using a string. The default string storage format is:: "%(hour)02d:%(minute)02d:%(second)02d.%(microsecond)06d" e.g.:: 12:05:57.10558 The storage format can be customized to some degree using the ``storage_format`` and ``regexp`` parameters, such as:: import re from sqlalchemy.dialects.sqlite import TIME t = TIME(storage_format="%(hour)02d-%(minute)02d-" "%(second)02d-%(microsecond)06d", regexp=re.compile("(\d+)-(\d+)-(\d+)-(?:-(\d+))?") ) :param storage_format: format string which will be applied to the dict with keys hour, minute, second, and microsecond. :param regexp: regular expression which will be applied to incoming result rows. If the regexp contains named groups, the resulting match dict is applied to the Python time() constructor as keyword arguments. Otherwise, if positional groups are used, the time() constructor is called with positional arguments via ``map(int, match_obj.groups(0))``. """ _storage_format = "%(hour)02d:%(minute)02d:%(second)02d.%(microsecond)06d" def __init__(self, args, *kwargs): truncate_microseconds = kwargs.pop("truncate_microseconds", False) super(TIME, self).__init__(args, kwargs) if truncate_microseconds: assert "storage_format" not in kwargs, ( "You can specify only " "one of truncate_microseconds or storage_format." ) assert "regexp" not in kwargs, ( "You can specify only one of " "truncate_microseconds or regexp." ) self._storage_format = "%(hour)02d:%(minute)02d:%(second)02d" def bind_processor(self, dialect): datetime_time = datetime.time format_ = self._storage_format def process(value): if value is None: return None elif isinstance(value, datetime_time): return format_ % { "hour": value.hour, "minute": value.minute, "second": value.second, "microsecond": value.microsecond, } else: raise TypeError( "SQLite Time type only accepts Python " "time objects as input." ) return process def result_processor(self, dialect, coltype): if self._reg: return processors.str_to_datetime_processor_factory( self._reg, datetime.time ) else: return processors.str_to_time colspecs = { sqltypes.Date: DATE, sqltypes.DateTime: DATETIME, sqltypes.JSON: _SQliteJson, sqltypes.JSON.JSONIndexType: JSONIndexType, sqltypes.JSON.JSONPathType: JSONPathType, sqltypes.Time: TIME, } ischema_names = { "BIGINT": sqltypes.BIGINT, "BLOB": sqltypes.BLOB, "BOOL": sqltypes.BOOLEAN, "BOOLEAN": sqltypes.BOOLEAN, "CHAR": sqltypes.CHAR, "DATE": sqltypes.DATE, "DATE_CHAR": sqltypes.DATE, "DATETIME": sqltypes.DATETIME, "DATETIME_CHAR": sqltypes.DATETIME, "DOUBLE": sqltypes.FLOAT, "DECIMAL": sqltypes.DECIMAL, "FLOAT": sqltypes.FLOAT, "INT": sqltypes.INTEGER, "INTEGER": sqltypes.INTEGER, "JSON": JSON, "NUMERIC": sqltypes.NUMERIC, "REAL": sqltypes.REAL, "SMALLINT": sqltypes.SMALLINT, "TEXT": sqltypes.TEXT, "TIME": sqltypes.TIME, "TIME_CHAR": sqltypes.TIME, "TIMESTAMP": sqltypes.TIMESTAMP, "VARCHAR": sqltypes.VARCHAR, "NVARCHAR": sqltypes.NVARCHAR, "NCHAR": sqltypes.NCHAR, } class SQLiteCompiler(compiler.SQLCompiler): extract_map = util.update_copy( compiler.SQLCompiler.extract_map, { "month": "%m", "day": "%d", "year": "%Y", "second": "%S", "hour": "%H", "doy": "%j", "minute": "%M", "epoch": "%s", "dow": "%w", "week": "%W", }, ) def visit_now_func(self, fn, kw): return "CURRENT_TIMESTAMP" def visit_localtimestamp_func(self, func, kw): return 'DATETIME(CURRENT_TIMESTAMP, "localtime")' def visit_true(self, expr, kw): return "1" def visit_false(self, expr, kw): return "0" def visit_char_length_func(self, fn, kw): return "length%s" % self.function_argspec(fn) def visit_cast(self, cast, kwargs): if self.dialect.supports_cast: return super(SQLiteCompiler, self).visit_cast(cast, kwargs) else: return self.process(cast.clause, kwargs) def visit_extract(self, extract, kw): try: return "CAST(STRFTIME('%s', %s) AS INTEGER)" % ( self.extract_map[extract.field], self.process(extract.expr, kw), ) except KeyError as err: util.raise_( exc.CompileError( "%s is not a valid extract argument." % extract.field ), replace_context=err, ) def limit_clause(self, select, kw): text = "" if select._limit_clause is not None: text += "\n LIMIT " + self.process(select._limit_clause, kw) if select._offset_clause is not None: if select._limit_clause is None: text += "\n LIMIT " + self.process(sql.literal(-1)) text += " OFFSET " + self.process(select._offset_clause, kw) else: text += " OFFSET " + self.process(sql.literal(0), kw) return text def for_update_clause(self, select, kw): # sqlite has no "FOR UPDATE" AFAICT return "" def visit_is_distinct_from_binary(self, binary, operator, kw): return "%s IS NOT %s" % ( self.process(binary.left), self.process(binary.right), ) def visit_isnot_distinct_from_binary(self, binary, operator, kw): return "%s IS %s" % ( self.process(binary.left), self.process(binary.right), ) def visit_json_getitem_op_binary(self, binary, operator, kw): if binary.type._type_affinity is sqltypes.JSON: expr = "JSON_QUOTE(JSON_EXTRACT(%s, %s))" else: expr = "JSON_EXTRACT(%s, %s)" return expr % ( self.process(binary.left, kw), self.process(binary.right, kw), ) def visit_json_path_getitem_op_binary(self, binary, operator, kw): if binary.type._type_affinity is sqltypes.JSON: expr = "JSON_QUOTE(JSON_EXTRACT(%s, %s))" else: expr = "JSON_EXTRACT(%s, %s)" return expr % ( self.process(binary.left, kw), self.process(binary.right, kw), ) def visit_empty_set_expr(self, element_types): return "SELECT %s FROM (SELECT %s) WHERE 1!=1" % ( ", ".join("1" for type_ in element_types or [INTEGER()]), ", ".join("1" for type_ in element_types or [INTEGER()]), ) class SQLiteDDLCompiler(compiler.DDLCompiler): def get_column_specification(self, column, kwargs): coltype = self.dialect.type_compiler.process( column.type, type_expression=column ) colspec = self.preparer.format_column(column) + " " + coltype default = self.get_column_default_string(column) if default is not None: if isinstance(column.server_default.arg, ColumnElement): default = "(" + default + ")" colspec += " DEFAULT " + default if not column.nullable: colspec += " NOT NULL" on_conflict_clause = column.dialect_options["sqlite"][ "on_conflict_not_null" ] if on_conflict_clause is not None: colspec += " ON CONFLICT " + on_conflict_clause if column.primary_key: if ( column.autoincrement is True and len(column.table.primary_key.columns) != 1 ): raise exc.CompileError( "SQLite does not support autoincrement for " "composite primary keys" ) if ( column.table.dialect_options["sqlite"]["autoincrement"] and len(column.table.primary_key.columns) == 1 and issubclass(column.type._type_affinity, sqltypes.Integer) and not column.foreign_keys ): colspec += " PRIMARY KEY" on_conflict_clause = column.dialect_options["sqlite"][ "on_conflict_primary_key" ] if on_conflict_clause is not None: colspec += " ON CONFLICT " + on_conflict_clause colspec += " AUTOINCREMENT" if column.computed is not None: colspec += " " + self.process(column.computed) return colspec def visit_primary_key_constraint(self, constraint): # for columns with sqlite_autoincrement=True, # the PRIMARY KEY constraint can only be inline # with the column itself. if len(constraint.columns) == 1: c = list(constraint)[0] if ( c.primary_key and c.table.dialect_options["sqlite"]["autoincrement"] and issubclass(c.type._type_affinity, sqltypes.Integer) and not c.foreign_keys ): return None text = super(SQLiteDDLCompiler, self).visit_primary_key_constraint( constraint ) on_conflict_clause = constraint.dialect_options["sqlite"][ "on_conflict" ] if on_conflict_clause is None and len(constraint.columns) == 1: on_conflict_clause = list(constraint)[0].dialect_options["sqlite"][ "on_conflict_primary_key" ] if on_conflict_clause is not None: text += " ON CONFLICT " + on_conflict_clause return text def visit_unique_constraint(self, constraint): text = super(SQLiteDDLCompiler, self).visit_unique_constraint( constraint ) on_conflict_clause = constraint.dialect_options["sqlite"][ "on_conflict" ] if on_conflict_clause is None and len(constraint.columns) == 1: col1 = list(constraint)[0] if isinstance(col1, schema.SchemaItem): on_conflict_clause = list(constraint)[0].dialect_options[ "sqlite" ]["on_conflict_unique"] if on_conflict_clause is not None: text += " ON CONFLICT " + on_conflict_clause return text def visit_check_constraint(self, constraint): text = super(SQLiteDDLCompiler, self).visit_check_constraint( constraint ) on_conflict_clause = constraint.dialect_options["sqlite"][ "on_conflict" ] if on_conflict_clause is not None: text += " ON CONFLICT " + on_conflict_clause return text def visit_column_check_constraint(self, constraint): text = super(SQLiteDDLCompiler, self).visit_column_check_constraint( constraint ) if constraint.dialect_options["sqlite"]["on_conflict"] is not None: raise exc.CompileError( "SQLite does not support on conflict clause for " "column check constraint" ) return text def visit_foreign_key_constraint(self, constraint): local_table = constraint.elements[0].parent.table remote_table = constraint.elements[0].column.table if local_table.schema != remote_table.schema: return None else: return super(SQLiteDDLCompiler, self).visit_foreign_key_constraint( constraint ) def define_constraint_remote_table(self, constraint, table, preparer): """Format the remote table clause of a CREATE CONSTRAINT clause.""" return preparer.format_table(table, use_schema=False) def visit_create_index( self, create, include_schema=False, include_table_schema=True ): index = create.element self._verify_index_table(index) preparer = self.preparer text = "CREATE " if index.unique: text += "UNIQUE " text += "INDEX %s ON %s (%s)" % ( self._prepared_index_name(index, include_schema=True), preparer.format_table(index.table, use_schema=False), ", ".join( self.sql_compiler.process( expr, include_table=False, literal_binds=True ) for expr in index.expressions ), ) whereclause = index.dialect_options["sqlite"]["where"] if whereclause is not None: where_compiled = self.sql_compiler.process( whereclause, include_table=False, literal_binds=True ) text += " WHERE " + where_compiled return text def post_create_table(self, table): if table.dialect_options["sqlite"]["with_rowid"] is False: return "\n WITHOUT ROWID" return "" class SQLiteTypeCompiler(compiler.GenericTypeCompiler): def visit_large_binary(self, type_, kw): return self.visit_BLOB(type_) def visit_DATETIME(self, type_, kw): if ( not isinstance(type_, _DateTimeMixin) or type_.format_is_text_affinity ): return super(SQLiteTypeCompiler, self).visit_DATETIME(type_) else: return "DATETIME_CHAR" def visit_DATE(self, type_, kw): if ( not isinstance(type_, _DateTimeMixin) or type_.format_is_text_affinity ): return super(SQLiteTypeCompiler, self).visit_DATE(type_) else: return "DATE_CHAR" def visit_TIME(self, type_, kw): if ( not isinstance(type_, _DateTimeMixin) or type_.format_is_text_affinity ): return super(SQLiteTypeCompiler, self).visit_TIME(type_) else: return "TIME_CHAR" def visit_JSON(self, type_, kw): # note this name provides NUMERIC affinity, not TEXT. # should not be an issue unless the JSON value consists of a single # numeric value. JSONTEXT can be used if this case is required. return "JSON" class SQLiteIdentifierPreparer(compiler.IdentifierPreparer): reserved_words = set( [ "add", "after", "all", "alter", "analyze", "and", "as", "asc", "attach", "autoincrement", "before", "begin", "between", "by", "cascade", "case", "cast", "check", "collate", "column", "commit", "conflict", "constraint", "create", "cross", "current_date", "current_time", "current_timestamp", "database", "default", "deferrable", "deferred", "delete", "desc", "detach", "distinct", "drop", "each", "else", "end", "escape", "except", "exclusive", "exists", "explain", "false", "fail", "for", "foreign", "from", "full", "glob", "group", "having", "if", "ignore", "immediate", "in", "index", "indexed", "initially", "inner", "insert", "instead", "intersect", "into", "is", "isnull", "join", "key", "left", "like", "limit", "match", "natural", "not", "notnull", "null", "of", "offset", "on", "or", "order", "outer", "plan", "pragma", "primary", "query", "raise", "references", "reindex", "rename", "replace", "restrict", "right", "rollback", "row", "select", "set", "table", "temp", "temporary", "then", "to", "transaction", "trigger", "true", "union", "unique", "update", "using", "vacuum", "values", "view", "virtual", "when", "where", ] ) class SQLiteExecutionContext(default.DefaultExecutionContext): @util.memoized_property def _preserve_raw_colnames(self): return ( not self.dialect._broken_dotted_colnames or self.execution_options.get("sqlite_raw_colnames", False) ) def _translate_colname(self, colname): # TODO: detect SQLite version 3.10.0 or greater; # see [ticket:3633] # adjust for dotted column names. SQLite # in the case of UNION may store col names as # "tablename.colname", or if using an attached database, # "database.tablename.colname", in cursor.description if not self._preserve_raw_colnames and "." in colname: return colname.split(".")[-1], colname else: return colname, None class SQLiteDialect(default.DefaultDialect): name = "sqlite" supports_alter = False supports_unicode_statements = True supports_unicode_binds = True supports_default_values = True supports_empty_insert = False supports_cast = True supports_multivalues_insert = True tuple_in_values = True default_paramstyle = "qmark" execution_ctx_cls = SQLiteExecutionContext statement_compiler = SQLiteCompiler ddl_compiler = SQLiteDDLCompiler type_compiler = SQLiteTypeCompiler preparer = SQLiteIdentifierPreparer ischema_names = ischema_names colspecs = colspecs isolation_level = None construct_arguments = [ ( sa_schema.Table, { "autoincrement": False, "with_rowid": True, }, ), (sa_schema.Index, {"where": None}), ( sa_schema.Column, { "on_conflict_primary_key": None, "on_conflict_not_null": None, "on_conflict_unique": None, }, ), (sa_schema.Constraint, {"on_conflict": None}), ] _broken_fk_pragma_quotes = False _broken_dotted_colnames = False @util.deprecated_params( _json_serializer=( "1.3.7", "The _json_serializer argument to the SQLite dialect has " "been renamed to the correct name of json_serializer. The old " "argument name will be removed in a future release.", ), _json_deserializer=( "1.3.7", "The _json_deserializer argument to the SQLite dialect has " "been renamed to the correct name of json_deserializer. The old " "argument name will be removed in a future release.", ), ) def __init__( self, isolation_level=None, native_datetime=False, json_serializer=None, json_deserializer=None, _json_serializer=None, _json_deserializer=None, kwargs ): default.DefaultDialect.__init__(self, kwargs) self.isolation_level = isolation_level if _json_serializer: json_serializer = _json_serializer if _json_deserializer: json_deserializer = _json_deserializer self._json_serializer = json_serializer self._json_deserializer = json_deserializer # this flag used by pysqlite dialect, and perhaps others in the # future, to indicate the driver is handling date/timestamp # conversions (and perhaps datetime/time as well on some hypothetical # driver ?) self.native_datetime = native_datetime if self.dbapi is not None: self.supports_right_nested_joins = ( self.dbapi.sqlite_version_info >= (3, 7, 16) ) self._broken_dotted_colnames = self.dbapi.sqlite_version_info < ( 3, 10, 0, ) self.supports_default_values = self.dbapi.sqlite_version_info >= ( 3, 3, 8, ) self.supports_cast = self.dbapi.sqlite_version_info >= (3, 2, 3) self.supports_multivalues_insert = ( # http://www.sqlite.org/releaselog/3_7_11.html self.dbapi.sqlite_version_info >= (3, 7, 11) ) # see http://www.sqlalchemy.org/trac/ticket/2568 # as well as http://www.sqlite.org/src/info/600482d161 self._broken_fk_pragma_quotes = self.dbapi.sqlite_version_info < ( 3, 6, 14, ) _isolation_lookup = {"READ UNCOMMITTED": 1, "SERIALIZABLE": 0} def set_isolation_level(self, connection, level): try: isolation_level = self._isolation_lookup[level.replace("_", " ")] except KeyError as err: util.raise_( exc.ArgumentError( "Invalid value '%s' for isolation_level. " "Valid isolation levels for %s are %s" % (level, self.name, ", ".join(self._isolation_lookup)) ), replace_context=err, ) cursor = connection.cursor() cursor.execute("PRAGMA read_uncommitted = %d" % isolation_level) cursor.close() def get_isolation_level(self, connection): cursor = connection.cursor() cursor.execute("PRAGMA read_uncommitted") res = cursor.fetchone() if res: value = res[0] else: # http://www.sqlite.org/changes.html#version_3_3_3 # "Optional READ UNCOMMITTED isolation (instead of the # default isolation level of SERIALIZABLE) and # table level locking when database connections # share a common cache."" # pre-SQLite 3.3.0 default to 0 value = 0 cursor.close() if value == 0: return "SERIALIZABLE" elif value == 1: return "READ UNCOMMITTED" else: assert False, "Unknown isolation level %s" % value def on_connect(self): if self.isolation_level is not None: def connect(conn): self.set_isolation_level(conn, self.isolation_level) return connect else: return None @reflection.cache def get_schema_names(self, connection, kw): s = "PRAGMA database_list" dl = connection.execute(s) return [db[1] for db in dl if db[1] != "temp"] @reflection.cache def get_table_names(self, connection, schema=None, kw): if schema is not None: qschema = self.identifier_preparer.quote_identifier(schema) master = "%s.sqlite_master" % qschema else: master = "sqlite_master" s = ("SELECT name FROM %s " "WHERE type='table' ORDER BY name") % ( master, ) rs = connection.execute(s) return [row[0] for row in rs] @reflection.cache def get_temp_table_names(self, connection, kw): s = ( "SELECT name FROM sqlite_temp_master " "WHERE type='table' ORDER BY name " ) rs = connection.execute(s) return [row[0] for row in rs] @reflection.cache def get_temp_view_names(self, connection, kw): s = ( "SELECT name FROM sqlite_temp_master " "WHERE type='view' ORDER BY name " ) rs = connection.execute(s) return [row[0] for row in rs] def has_table(self, connection, table_name, schema=None): info = self._get_table_pragma( connection, "table_info", table_name, schema=schema ) return bool(info) @reflection.cache def get_view_names(self, connection, schema=None, kw): if schema is not None: qschema = self.identifier_preparer.quote_identifier(schema) master = "%s.sqlite_master" % qschema else: master = "sqlite_master" s = ("SELECT name FROM %s " "WHERE type='view' ORDER BY name") % ( master, ) rs = connection.execute(s) return [row[0] for row in rs] @reflection.cache def get_view_definition(self, connection, view_name, schema=None, kw): if schema is not None: qschema = self.identifier_preparer.quote_identifier(schema) master = "%s.sqlite_master" % qschema s = ("SELECT sql FROM %s WHERE name = ? AND type='view'") % ( master, ) rs = connection.execute(s, (view_name,)) else: try: s = ( "SELECT sql FROM " " (SELECT * FROM sqlite_master UNION ALL " " SELECT * FROM sqlite_temp_master) " "WHERE name = ? " "AND type='view'" ) rs = connection.execute(s, (view_name,)) except exc.DBAPIError: s = ( "SELECT sql FROM sqlite_master WHERE name = ? " "AND type='view'" ) rs = connection.execute(s, (view_name,)) result = rs.fetchall() if result: return result[0].sql @reflection.cache def get_columns(self, connection, table_name, schema=None, kw): pragma = "table_info" # computed columns are threaded as hidden, they require table_xinfo if self.server_version_info >= (3, 31): pragma = "table_xinfo" info = self._get_table_pragma( connection, pragma, table_name, schema=schema ) columns = [] tablesql = None for row in info: name = row[1] type_ = row[2].upper() nullable = not row[3] default = row[4] primary_key = row[5] hidden = row[6] if pragma == "table_xinfo" else 0 # hidden has value 0 for normal columns, 1 for hidden columns, # 2 for computed virtual columns and 3 for computed stored columns # https://www.sqlite.org/src/info/069351b85f9a706f60d3e98fbc8aaf40c374356b967c0464aede30ead3d9d18b if hidden == 1: continue generated = bool(hidden) persisted = hidden == 3 if tablesql is None and generated: tablesql = self._get_table_sql( connection, table_name, schema, kw ) columns.append( self._get_column_info( name, type_, nullable, default, primary_key, generated, persisted, tablesql, ) ) return columns def _get_column_info( self, name, type_, nullable, default, primary_key, generated, persisted, tablesql, ): if generated: # the type of a column "cc INTEGER GENERATED ALWAYS AS (1 + 42)" # somehow is "INTEGER GENERATED ALWAYS" type_ = re.sub("generated", "", type_, flags=re.IGNORECASE) type_ = re.sub("always", "", type_, flags=re.IGNORECASE).strip() coltype = self._resolve_type_affinity(type_) if default is not None: default = util.text_type(default) colspec = { "name": name, "type": coltype, "nullable": nullable, "default": default, "autoincrement": "auto", "primary_key": primary_key, } if generated: sqltext = "" if tablesql: pattern = r"[^,]\s+AS\s+\(([^,])\)\s(?:virtual\|stored)?" match = re.search( re.escape(name) + pattern, tablesql, re.IGNORECASE ) if match: sqltext = match.group(1) colspec["computed"] = {"sqltext": sqltext, "persisted": persisted} return colspec def _resolve_type_affinity(self, type_): """Return a data type from a reflected column, using affinity tules. SQLite's goal for universal compatibility introduces some complexity during reflection, as a column's defined type might not actually be a type that SQLite understands - or indeed, my not be defined at all. Internally, SQLite handles this with a 'data type affinity' for each column definition, mapping to one of 'TEXT', 'NUMERIC', 'INTEGER', 'REAL', or 'NONE' (raw bits). The algorithm that determines this is listed in http://www.sqlite.org/datatype3.html section 2.1. This method allows SQLAlchemy to support that algorithm, while still providing access to smarter reflection utilities by regcognizing column definitions that SQLite only supports through affinity (like DATE and DOUBLE). """ match = re.match(r"([\w ]+)(\(.?\))?", type_) if match: coltype = match.group(1) args = match.group(2) else: coltype = "" args = "" if coltype in self.ischema_names: coltype = self.ischema_names[coltype] elif "INT" in coltype: coltype = sqltypes.INTEGER elif "CHAR" in coltype or "CLOB" in coltype or "TEXT" in coltype: coltype = sqltypes.TEXT elif "BLOB" in coltype or not coltype: coltype = sqltypes.NullType elif "REAL" in coltype or "FLOA" in coltype or "DOUB" in coltype: coltype = sqltypes.REAL else: coltype = sqltypes.NUMERIC if args is not None: args = re.findall(r"(\d+)", args) try: coltype = coltype([int(a) for a in args]) except TypeError: util.warn( "Could not instantiate type %s with " "reflected arguments %s; using no arguments." % (coltype, args) ) coltype = coltype() else: coltype = coltype() return coltype @reflection.cache def get_pk_constraint(self, connection, table_name, schema=None, kw): constraint_name = None table_data = self._get_table_sql(connection, table_name, schema=schema) if table_data: PK_PATTERN = r"CONSTRAINT (\w+) PRIMARY KEY" result = re.search(PK_PATTERN, table_data, re.I) constraint_name = result.group(1) if result else None cols = self.get_columns(connection, table_name, schema, kw) cols.sort(key=lambda col: col.get("primary_key")) pkeys = [] for col in cols: if col["primary_key"]: pkeys.append(col["name"]) return {"constrained_columns": pkeys, "name": constraint_name} @reflection.cache def get_foreign_keys(self, connection, table_name, schema=None, kw): # sqlite makes this extremely difficult. # First, use the pragma to get the actual FKs. pragma_fks = self._get_table_pragma( connection, "foreign_key_list", table_name, schema=schema ) fks = {} for row in pragma_fks: (numerical_id, rtbl, lcol, rcol) = (row[0], row[2], row[3], row[4]) if not rcol: # no referred column, which means it was not named in the # original DDL. The referred columns of the foreign key # constraint are therefore the primary key of the referred # table. referred_pk = self.get_pk_constraint( connection, rtbl, schema=schema, kw ) # note that if table doesnt exist, we still get back a record, # just it has no columns in it referred_columns = referred_pk["constrained_columns"] else: # note we use this list only if this is the first column # in the constraint. for subsequent columns we ignore the # list and append "rcol" if present. referred_columns = [] if self._broken_fk_pragma_quotes: rtbl = re.sub(r"^[\"\[`\']\|[\"\]`\']$", "", rtbl) if numerical_id in fks: fk = fks[numerical_id] else: fk = fks[numerical_id] = { "name": None, "constrained_columns": [], "referred_schema": schema, "referred_table": rtbl, "referred_columns": referred_columns, "options": {}, } fks[numerical_id] = fk fk["constrained_columns"].append(lcol) if rcol: fk["referred_columns"].append(rcol) def fk_sig(constrained_columns, referred_table, referred_columns): return ( tuple(constrained_columns) + (referred_table,) + tuple(referred_columns) ) # then, parse the actual SQL and attempt to find DDL that matches # the names as well. SQLite saves the DDL in whatever format # it was typed in as, so need to be liberal here. keys_by_signature = dict( ( fk_sig( fk["constrained_columns"], fk["referred_table"], fk["referred_columns"], ), fk, ) for fk in fks.values() ) table_data = self._get_table_sql(connection, table_name, schema=schema) if table_data is None: # system tables, etc. return [] def parse_fks(): FK_PATTERN = ( r"(?:CONSTRAINT (\w+) +)?" r"FOREIGN KEY \( (.+?) \) +" r'REFERENCES +(?:(?:"(.+?)")\|([a-z0-9_]+)) \((.+?)\) ' r"((?:ON (?:DELETE\|UPDATE) " r"(?:SET NULL\|SET DEFAULT\|CASCADE\|RESTRICT\|NO ACTION) ))" ) for match in re.finditer(FK_PATTERN, table_data, re.I): ( constraint_name, constrained_columns, referred_quoted_name, referred_name, referred_columns, onupdatedelete, ) = match.group(1, 2, 3, 4, 5, 6) constrained_columns = list( self._find_cols_in_sig(constrained_columns) ) if not referred_columns: referred_columns = constrained_columns else: referred_columns = list( self._find_cols_in_sig(referred_columns) ) referred_name = referred_quoted_name or referred_name options = {} for token in re.split(r" \bON\b ", onupdatedelete.upper()): if token.startswith("DELETE"): options["ondelete"] = token[6:].strip() elif token.startswith("UPDATE"): options["onupdate"] = token[6:].strip() yield ( constraint_name, constrained_columns, referred_name, referred_columns, options, ) fkeys = [] for ( constraint_name, constrained_columns, referred_name, referred_columns, options, ) in parse_fks(): sig = fk_sig(constrained_columns, referred_name, referred_columns) if sig not in keys_by_signature: util.warn( "WARNING: SQL-parsed foreign key constraint " "'%s' could not be located in PRAGMA " "foreign_keys for table %s" % (sig, table_name) ) continue key = keys_by_signature.pop(sig) key["name"] = constraint_name key["options"] = options fkeys.append(key) # assume the remainders are the unnamed, inline constraints, just # use them as is as it's extremely difficult to parse inline # constraints fkeys.extend(keys_by_signature.values()) return fkeys def _find_cols_in_sig(self, sig): for match in re.finditer(r'(?:"(.+?)")\|([a-z0-9_]+)', sig, re.I): yield match.group(1) or match.group(2) @reflection.cache def get_unique_constraints( self, connection, table_name, schema=None, kw ): auto_index_by_sig = {} for idx in self.get_indexes( connection, table_name, schema=schema, include_auto_indexes=True, kw ): if not idx["name"].startswith("sqlite_autoindex"): continue sig = tuple(idx["column_names"]) auto_index_by_sig[sig] = idx table_data = self._get_table_sql( connection, table_name, schema=schema, *kw ) if not table_data: return [] unique_constraints = [] def parse_uqs(): UNIQUE_PATTERN = r'(?:CONSTRAINT "?(.+?)"? +)?UNIQUE \((.+?)\)' INLINE_UNIQUE_PATTERN = ( r'(?:(".+?")\|([a-z0-9]+)) ' r"+[a-z0-9_ ]+? +UNIQUE" ) for match in re.finditer(UNIQUE_PATTERN, table_data, re.I): name, cols = match.group(1, 2) yield name, list(self._find_cols_in_sig(cols)) # we need to match inlines as well, as we seek to differentiate # a UNIQUE constraint from a UNIQUE INDEX, even though these # are kind of the same thing :) for match in re.finditer(INLINE_UNIQUE_PATTERN, table_data, re.I): cols = list( self._find_cols_in_sig(match.group(1) or match.group(2)) ) yield None, cols for name, cols in parse_uqs(): sig = tuple(cols) if sig in auto_index_by_sig: auto_index_by_sig.pop(sig) parsed_constraint = {"name": name, "column_names": cols} unique_constraints.append(parsed_constraint) # NOTE: auto_index_by_sig might not be empty here, # the PRIMARY KEY may have an entry. return unique_constraints @reflection.cache def get_check_constraints(self, connection, table_name, schema=None, kw): table_data = self._get_table_sql( connection, table_name, schema=schema, kw ) if not table_data: return [] CHECK_PATTERN = r"(?:CONSTRAINT (\w+) +)?" r"CHECK \( (.+) \),? " check_constraints = [] # NOTE: we aren't using re.S here because we actually are # taking advantage of each CHECK constraint being all on one # line in the table definition in order to delineate. This # necessarily makes assumptions as to how the CREATE TABLE # was emitted. for match in re.finditer(CHECK_PATTERN, table_data, re.I): check_constraints.append( {"sqltext": match.group(2), "name": match.group(1)} ) return check_constraints @reflection.cache def get_indexes(self, connection, table_name, schema=None, kw): pragma_indexes = self._get_table_pragma( connection, "index_list", table_name, schema=schema ) indexes = [] include_auto_indexes = kw.pop("include_auto_indexes", False) for row in pragma_indexes: # ignore implicit primary key index. # http://www.mail-archive.com/sqlite-users@sqlite.org/msg30517.html if not include_auto_indexes and row[1].startswith( "sqlite_autoindex" ): continue indexes.append(dict(name=row[1], column_names=[], unique=row[2])) # loop thru unique indexes to get the column names. for idx in list(indexes): pragma_index = self._get_table_pragma( connection, "index_info", idx["name"] ) for row in pragma_index: if row[2] is None: util.warn( "Skipped unsupported reflection of " "expression-based index %s" % idx["name"] ) indexes.remove(idx) break else: idx["column_names"].append(row[2]) return indexes @reflection.cache def _get_table_sql(self, connection, table_name, schema=None, kw): if schema: schema_expr = "%s." % ( self.identifier_preparer.quote_identifier(schema) ) else: schema_expr = "" try: s = ( "SELECT sql FROM " " (SELECT * FROM %(schema)ssqlite_master UNION ALL " " SELECT * FROM %(schema)ssqlite_temp_master) " "WHERE name = ? " "AND type = 'table'" % {"schema": schema_expr} ) rs = connection.execute(s, (table_name,)) except exc.DBAPIError: s = ( "SELECT sql FROM %(schema)ssqlite_master " "WHERE name = ? " "AND type = 'table'" % {"schema": schema_expr} ) rs = connection.execute(s, (table_name,)) return rs.scalar() def _get_table_pragma(self, connection, pragma, table_name, schema=None): quote = self.identifier_preparer.quote_identifier if schema is not None: statements = ["PRAGMA %s." % quote(schema)] else: # because PRAGMA looks in all attached databases if no schema # given, need to specify "main" schema, however since we want # 'temp' tables in the same namespace as 'main', need to run # the PRAGMA twice statements = ["PRAGMA main.", "PRAGMA temp."] qtable = quote(table_name) for statement in statements: statement = "%s%s(%s)" % (statement, pragma, qtable) cursor = connection.execute(statement) if not cursor._soft_closed: # work around SQLite issue whereby cursor.description # is blank when PRAGMA returns no rows: # http://www.sqlite.org/cvstrac/tktview?tn=1884 result = cursor.fetchall() else: result = [] if result: return result else: return []	73.46 KB	2026-01-20 12:58
📄 json.py from ... import types as sqltypes class JSON(sqltypes.JSON): """SQLite JSON type. SQLite supports JSON as of version 3.9 through its JSON1_ extension. Note that JSON1_ is a `loadable extension <https://www.sqlite.org/loadext.html>`_ and as such may not be available, or may require run-time loading. The :class:`_sqlite.JSON` type supports persistence of JSON values as well as the core index operations provided by :class:`_types.JSON` datatype, by adapting the operations to render the ``JSON_EXTRACT`` function wrapped in the ``JSON_QUOTE`` function at the database level. Extracted values are quoted in order to ensure that the results are always JSON string values. .. versionadded:: 1.3 .. seealso:: JSON1_ .. _JSON1: https://www.sqlite.org/json1.html """ # Note: these objects currently match exactly those of MySQL, however since # these are not generalizable to all JSON implementations, remain separately # implemented for each dialect. class _FormatTypeMixin(object): def _format_value(self, value): raise NotImplementedError() def bind_processor(self, dialect): super_proc = self.string_bind_processor(dialect) def process(value): value = self._format_value(value) if super_proc: value = super_proc(value) return value return process def literal_processor(self, dialect): super_proc = self.string_literal_processor(dialect) def process(value): value = self._format_value(value) if super_proc: value = super_proc(value) return value return process class JSONIndexType(_FormatTypeMixin, sqltypes.JSON.JSONIndexType): def _format_value(self, value): if isinstance(value, int): value = "$[%s]" % value else: value = '$."%s"' % value return value class JSONPathType(_FormatTypeMixin, sqltypes.JSON.JSONPathType): def _format_value(self, value): return "$%s" % ( "".join( [ "[%s]" % elem if isinstance(elem, int) else '."%s"' % elem for elem in value ] ) )	2.24 KB	2026-01-20 12:58
📄 provision.py import os from ...engine import url as sa_url from ...testing.provision import create_db from ...testing.provision import drop_db from ...testing.provision import follower_url_from_main from ...testing.provision import log from ...testing.provision import post_configure_engine from ...testing.provision import run_reap_dbs from ...testing.provision import temp_table_keyword_args @follower_url_from_main.for_db("sqlite") def _sqlite_follower_url_from_main(url, ident): url = sa_url.make_url(url) if not url.database or url.database == ":memory:": return url else: return sa_url.make_url("sqlite:///%s.db" % ident) @post_configure_engine.for_db("sqlite") def _sqlite_post_configure_engine(url, engine, follower_ident): from sqlalchemy import event @event.listens_for(engine, "connect") def connect(dbapi_connection, connection_record): # use file DBs in all cases, memory acts kind of strangely # as an attached if not follower_ident: # note this test_schema.db gets created for all test runs. # there's not any dedicated cleanup step for it. it in some # ways corresponds to the "test.test_schema" schema that's # expected to be already present, so for now it just stays # in a given checkout directory. dbapi_connection.execute( 'ATTACH DATABASE "test_schema.db" AS test_schema' ) else: dbapi_connection.execute( 'ATTACH DATABASE "%s_test_schema.db" AS test_schema' % follower_ident ) @create_db.for_db("sqlite") def _sqlite_create_db(cfg, eng, ident): pass @drop_db.for_db("sqlite") def _sqlite_drop_db(cfg, eng, ident): for path in ["%s.db" % ident, "%s_test_schema.db" % ident]: if os.path.exists(path): log.info("deleting SQLite database file: %s" % path) os.remove(path) @temp_table_keyword_args.for_db("sqlite") def _sqlite_temp_table_keyword_args(cfg, eng): return {"prefixes": ["TEMPORARY"]} @run_reap_dbs.for_db("sqlite") def _reap_sqlite_dbs(url, idents): log.info("db reaper connecting to %r", url) log.info("identifiers in file: %s", ", ".join(idents)) for ident in idents: # we don't have a config so we can't call _sqlite_drop_db due to the # decorator for path in ["%s.db" % ident, "%s_test_schema.db" % ident]: if os.path.exists(path): log.info("deleting SQLite database file: %s" % path) os.remove(path)	2.53 KB	2026-01-20 12:58
📄 pysqlcipher.py # sqlite/pysqlcipher.py # Copyright (C) 2005-2021 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 """ .. dialect:: sqlite+pysqlcipher :name: pysqlcipher :dbapi: pysqlcipher :connectstring: sqlite+pysqlcipher://:passphrase/file_path[?kdf_iter=<iter>] :url: https://pypi.python.org/pypi/pysqlcipher ``pysqlcipher`` is a fork of the standard ``pysqlite`` driver to make use of the `SQLCipher <https://www.zetetic.net/sqlcipher>`_ backend. ``pysqlcipher3`` is a fork of ``pysqlcipher`` for Python 3. This dialect will attempt to import it if ``pysqlcipher`` is non-present. .. versionadded:: 1.1.4 - added fallback import for pysqlcipher3 .. versionadded:: 0.9.9 - added pysqlcipher dialect Driver ------ The driver here is the `pysqlcipher <https://pypi.python.org/pypi/pysqlcipher>`_ driver, which makes use of the SQLCipher engine. This system essentially introduces new PRAGMA commands to SQLite which allows the setting of a passphrase and other encryption parameters, allowing the database file to be encrypted. `pysqlcipher3` is a fork of `pysqlcipher` with support for Python 3, the driver is the same. Connect Strings --------------- The format of the connect string is in every way the same as that of the :mod:`~sqlalchemy.dialects.sqlite.pysqlite` driver, except that the "password" field is now accepted, which should contain a passphrase:: e = create_engine('sqlite+pysqlcipher://:testing@/foo.db') For an absolute file path, two leading slashes should be used for the database name:: e = create_engine('sqlite+pysqlcipher://:testing@//path/to/foo.db') A selection of additional encryption-related pragmas supported by SQLCipher as documented at https://www.zetetic.net/sqlcipher/sqlcipher-api/ can be passed in the query string, and will result in that PRAGMA being called for each new connection. Currently, ``cipher``, ``kdf_iter`` ``cipher_page_size`` and ``cipher_use_hmac`` are supported:: e = create_engine('sqlite+pysqlcipher://:testing@/foo.db?cipher=aes-256-cfb&kdf_iter=64000') Pooling Behavior ---------------- The driver makes a change to the default pool behavior of pysqlite as described in :ref:`pysqlite_threading_pooling`. The pysqlcipher driver has been observed to be significantly slower on connection than the pysqlite driver, most likely due to the encryption overhead, so the dialect here defaults to using the :class:`.SingletonThreadPool` implementation, instead of the :class:`.NullPool` pool used by pysqlite. As always, the pool implementation is entirely configurable using the :paramref:`_sa.create_engine.poolclass` parameter; the :class:`.StaticPool` may be more feasible for single-threaded use, or :class:`.NullPool` may be used to prevent unencrypted connections from being held open for long periods of time, at the expense of slower startup time for new connections. """ # noqa from __future__ import absolute_import from .pysqlite import SQLiteDialect_pysqlite from ... import pool from ...engine import url as _url class SQLiteDialect_pysqlcipher(SQLiteDialect_pysqlite): driver = "pysqlcipher" pragmas = ("kdf_iter", "cipher", "cipher_page_size", "cipher_use_hmac") @classmethod def dbapi(cls): try: from pysqlcipher import dbapi2 as sqlcipher except ImportError as e: try: from pysqlcipher3 import dbapi2 as sqlcipher except ImportError: raise e return sqlcipher @classmethod def get_pool_class(cls, url): return pool.SingletonThreadPool def connect(self, cargs, cparams): passphrase = cparams.pop("passphrase", "") pragmas = dict((key, cparams.pop(key, None)) for key in self.pragmas) conn = super(SQLiteDialect_pysqlcipher, self).connect( cargs, **cparams ) conn.execute('pragma key="%s"' % passphrase) for prag, value in pragmas.items(): if value is not None: conn.execute('pragma %s="%s"' % (prag, value)) return conn def create_connect_args(self, url): super_url = _url.URL( url.drivername, username=url.username, host=url.host, database=url.database, query=url.query, ) c_args, opts = super( SQLiteDialect_pysqlcipher, self ).create_connect_args(super_url) opts["passphrase"] = url.password return c_args, opts dialect = SQLiteDialect_pysqlcipher	4.58 KB	2026-01-20 12:58
📄 pysqlite.py # sqlite/pysqlite.py # Copyright (C) 2005-2021 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 r""" .. dialect:: sqlite+pysqlite :name: pysqlite :dbapi: sqlite3 :connectstring: sqlite+pysqlite:///file_path :url: http://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 specifing "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 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 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.execute("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 <http://sqlite.org/lang_transaction.html>`_, by adding the desired locking mode to our ``"BEGIN"``:: @event.listens_for(engine, "begin") def do_begin(conn): conn.execute("BEGIN EXCLUSIVE") .. seealso:: `BEGIN TRANSACTION <http://sqlite.org/lang_transaction.html>`_ - on the SQLite site `sqlite3 SELECT does not BEGIN a transaction <http://bugs.python.org/issue9924>`_ - on the Python bug tracker `sqlite3 module breaks transactions and potentially corrupts data <http://bugs.python.org/issue10740>`_ - on the Python bug tracker """ # noqa import os 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" 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:": 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 def set_isolation_level(self, connection, level): if hasattr(connection, "connection"): dbapi_connection = connection.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 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 = opts.copy() # 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	20.49 KB	2026-01-20 12:58

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