# dialects/mssql/base.py # Copyright (C) 2005-2024 the SQLAlchemy authors and contributors # # # This module is part of SQLAlchemy and is released under # the MIT License: https://www.opensource.org/licenses/mit-license.php # mypy: ignore-errors """ .. dialect:: mssql :name: Microsoft SQL Server :full_support: 2017 :normal_support: 2012+ :best_effort: 2005+ .. _mssql_external_dialects: External Dialects ----------------- In addition to the above DBAPI layers with native SQLAlchemy support, there are third-party dialects for other DBAPI layers that are compatible with SQL Server. See the "External Dialects" list on the :ref:`dialect_toplevel` page. .. _mssql_identity: Auto Increment Behavior / IDENTITY Columns ------------------------------------------ SQL Server provides so-called "auto incrementing" behavior using the ``IDENTITY`` construct, which can be placed on any single integer column in a table. SQLAlchemy considers ``IDENTITY`` within its default "autoincrement" behavior for an integer primary key column, described at :paramref:`_schema.Column.autoincrement`. This means that by default, the first integer primary key column in a :class:`_schema.Table` will be considered to be the identity column - unless it is associated with a :class:`.Sequence` - and will generate DDL as such:: from sqlalchemy import Table, MetaData, Column, Integer m = MetaData() t = Table('t', m, Column('id', Integer, primary_key=True), Column('x', Integer)) m.create_all(engine) The above example will generate DDL as: .. sourcecode:: sql CREATE TABLE t ( id INTEGER NOT NULL IDENTITY, x INTEGER NULL, PRIMARY KEY (id) ) For the case where this default generation of ``IDENTITY`` is not desired, specify ``False`` for the :paramref:`_schema.Column.autoincrement` flag, on the first integer primary key column:: m = MetaData() t = Table('t', m, Column('id', Integer, primary_key=True, autoincrement=False), Column('x', Integer)) m.create_all(engine) To add the ``IDENTITY`` keyword to a non-primary key column, specify ``True`` for the :paramref:`_schema.Column.autoincrement` flag on the desired :class:`_schema.Column` object, and ensure that :paramref:`_schema.Column.autoincrement` is set to ``False`` on any integer primary key column:: m = MetaData() t = Table('t', m, Column('id', Integer, primary_key=True, autoincrement=False), Column('x', Integer, autoincrement=True)) m.create_all(engine) .. versionchanged:: 1.4 Added :class:`_schema.Identity` construct in a :class:`_schema.Column` to specify the start and increment parameters of an IDENTITY. These replace the use of the :class:`.Sequence` object in order to specify these values. .. deprecated:: 1.4 The ``mssql_identity_start`` and ``mssql_identity_increment`` parameters to :class:`_schema.Column` are deprecated and should we replaced by an :class:`_schema.Identity` object. Specifying both ways of configuring an IDENTITY will result in a compile error. These options are also no longer returned as part of the ``dialect_options`` key in :meth:`_reflection.Inspector.get_columns`. Use the information in the ``identity`` key instead. .. deprecated:: 1.3 The use of :class:`.Sequence` to specify IDENTITY characteristics is deprecated and will be removed in a future release. Please use the :class:`_schema.Identity` object parameters :paramref:`_schema.Identity.start` and :paramref:`_schema.Identity.increment`. .. versionchanged:: 1.4 Removed the ability to use a :class:`.Sequence` object to modify IDENTITY characteristics. :class:`.Sequence` objects now only manipulate true T-SQL SEQUENCE types. .. note:: There can only be one IDENTITY column on the table. When using ``autoincrement=True`` to enable the IDENTITY keyword, SQLAlchemy does not guard against multiple columns specifying the option simultaneously. The SQL Server database will instead reject the ``CREATE TABLE`` statement. .. note:: An INSERT statement which attempts to provide a value for a column that is marked with IDENTITY will be rejected by SQL Server. In order for the value to be accepted, a session-level option "SET IDENTITY_INSERT" must be enabled. The SQLAlchemy SQL Server dialect will perform this operation automatically when using a core :class:`_expression.Insert` construct; if the execution specifies a value for the IDENTITY column, the "IDENTITY_INSERT" option will be enabled for the span of that statement's invocation.However, this scenario is not high performing and should not be relied upon for normal use. If a table doesn't actually require IDENTITY behavior in its integer primary key column, the keyword should be disabled when creating the table by ensuring that ``autoincrement=False`` is set. Controlling "Start" and "Increment" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Specific control over the "start" and "increment" values for the ``IDENTITY`` generator are provided using the :paramref:`_schema.Identity.start` and :paramref:`_schema.Identity.increment` parameters passed to the :class:`_schema.Identity` object:: from sqlalchemy import Table, Integer, Column, Identity test = Table( 'test', metadata, Column( 'id', Integer, primary_key=True, Identity(start=100, increment=10) ), Column('name', String(20)) ) The CREATE TABLE for the above :class:`_schema.Table` object would be: .. sourcecode:: sql CREATE TABLE test ( id INTEGER NOT NULL IDENTITY(100,10) PRIMARY KEY, name VARCHAR(20) NULL, ) .. note:: The :class:`_schema.Identity` object supports many other parameter in addition to ``start`` and ``increment``. These are not supported by SQL Server and will be ignored when generating the CREATE TABLE ddl. .. versionchanged:: 1.3.19 The :class:`_schema.Identity` object is now used to affect the ``IDENTITY`` generator for a :class:`_schema.Column` under SQL Server. Previously, the :class:`.Sequence` object was used. As SQL Server now supports real sequences as a separate construct, :class:`.Sequence` will be functional in the normal way starting from SQLAlchemy version 1.4. Using IDENTITY with Non-Integer numeric types ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ SQL Server also allows ``IDENTITY`` to be used with ``NUMERIC`` columns. To implement this pattern smoothly in SQLAlchemy, the primary datatype of the column should remain as ``Integer``, however the underlying implementation type deployed to the SQL Server database can be specified as ``Numeric`` using :meth:`.TypeEngine.with_variant`:: from sqlalchemy import Column from sqlalchemy import Integer from sqlalchemy import Numeric from sqlalchemy import String from sqlalchemy.ext.declarative import declarative_base Base = declarative_base() class TestTable(Base): __tablename__ = "test" id = Column( Integer().with_variant(Numeric(10, 0), "mssql"), primary_key=True, autoincrement=True, ) name = Column(String) In the above example, ``Integer().with_variant()`` provides clear usage information that accurately describes the intent of the code. The general restriction that ``autoincrement`` only applies to ``Integer`` is established at the metadata level and not at the per-dialect level. When using the above pattern, the primary key identifier that comes back from the insertion of a row, which is also the value that would be assigned to an ORM object such as ``TestTable`` above, will be an instance of ``Decimal()`` and not ``int`` when using SQL Server. The numeric return type of the :class:`_types.Numeric` type can be changed to return floats by passing False to :paramref:`_types.Numeric.asdecimal`. To normalize the return type of the above ``Numeric(10, 0)`` to return Python ints (which also support "long" integer values in Python 3), use :class:`_types.TypeDecorator` as follows:: from sqlalchemy import TypeDecorator class NumericAsInteger(TypeDecorator): '''normalize floating point return values into ints''' impl = Numeric(10, 0, asdecimal=False) cache_ok = True def process_result_value(self, value, dialect): if value is not None: value = int(value) return value class TestTable(Base): __tablename__ = "test" id = Column( Integer().with_variant(NumericAsInteger, "mssql"), primary_key=True, autoincrement=True, ) name = Column(String) .. _mssql_insert_behavior: INSERT behavior ^^^^^^^^^^^^^^^^ Handling of the ``IDENTITY`` column at INSERT time involves two key techniques. The most common is being able to fetch the "last inserted value" for a given ``IDENTITY`` column, a process which SQLAlchemy performs implicitly in many cases, most importantly within the ORM. The process for fetching this value has several variants: * In the vast majority of cases, RETURNING is used in conjunction with INSERT statements on SQL Server in order to get newly generated primary key values: .. sourcecode:: sql INSERT INTO t (x) OUTPUT inserted.id VALUES (?) As of SQLAlchemy 2.0, the :ref:`engine_insertmanyvalues` feature is also used by default to optimize many-row INSERT statements; for SQL Server the feature takes place for both RETURNING and-non RETURNING INSERT statements. .. versionchanged:: 2.0.10 The :ref:`engine_insertmanyvalues` feature for SQL Server was temporarily disabled for SQLAlchemy version 2.0.9 due to issues with row ordering. As of 2.0.10 the feature is re-enabled, with special case handling for the unit of work's requirement for RETURNING to be ordered. * When RETURNING is not available or has been disabled via ``implicit_returning=False``, either the ``scope_identity()`` function or the ``@@identity`` variable is used; behavior varies by backend: * when using PyODBC, the phrase ``; select scope_identity()`` will be appended to the end of the INSERT statement; a second result set will be fetched in order to receive the value. Given a table as:: t = Table( 't', metadata, Column('id', Integer, primary_key=True), Column('x', Integer), implicit_returning=False ) an INSERT will look like: .. sourcecode:: sql INSERT INTO t (x) VALUES (?); select scope_identity() * Other dialects such as pymssql will call upon ``SELECT scope_identity() AS lastrowid`` subsequent to an INSERT statement. If the flag ``use_scope_identity=False`` is passed to :func:`_sa.create_engine`, the statement ``SELECT @@identity AS lastrowid`` is used instead. A table that contains an ``IDENTITY`` column will prohibit an INSERT statement that refers to the identity column explicitly. The SQLAlchemy dialect will detect when an INSERT construct, created using a core :func:`_expression.insert` construct (not a plain string SQL), refers to the identity column, and in this case will emit ``SET IDENTITY_INSERT ON`` prior to the insert statement proceeding, and ``SET IDENTITY_INSERT OFF`` subsequent to the execution. Given this example:: m = MetaData() t = Table('t', m, Column('id', Integer, primary_key=True), Column('x', Integer)) m.create_all(engine) with engine.begin() as conn: conn.execute(t.insert(), {'id': 1, 'x':1}, {'id':2, 'x':2}) The above column will be created with IDENTITY, however the INSERT statement we emit is specifying explicit values. In the echo output we can see how SQLAlchemy handles this: .. sourcecode:: sql CREATE TABLE t ( id INTEGER NOT NULL IDENTITY(1,1), x INTEGER NULL, PRIMARY KEY (id) ) COMMIT SET IDENTITY_INSERT t ON INSERT INTO t (id, x) VALUES (?, ?) ((1, 1), (2, 2)) SET IDENTITY_INSERT t OFF COMMIT This is an auxiliary use case suitable for testing and bulk insert scenarios. SEQUENCE support ---------------- The :class:`.Sequence` object creates "real" sequences, i.e., ``CREATE SEQUENCE``: .. sourcecode:: pycon+sql >>> from sqlalchemy import Sequence >>> from sqlalchemy.schema import CreateSequence >>> from sqlalchemy.dialects import mssql >>> print(CreateSequence(Sequence("my_seq", start=1)).compile(dialect=mssql.dialect())) {printsql}CREATE SEQUENCE my_seq START WITH 1 For integer primary key generation, SQL Server's ``IDENTITY`` construct should generally be preferred vs. sequence. .. tip:: The default start value for T-SQL is ``-2**63`` instead of 1 as in most other SQL databases. Users should explicitly set the :paramref:`.Sequence.start` to 1 if that's the expected default:: seq = Sequence("my_sequence", start=1) .. versionadded:: 1.4 added SQL Server support for :class:`.Sequence` .. versionchanged:: 2.0 The SQL Server dialect will no longer implicitly render "START WITH 1" for ``CREATE SEQUENCE``, which was the behavior first implemented in version 1.4. MAX on VARCHAR / NVARCHAR ------------------------- SQL Server supports the special string "MAX" within the :class:`_types.VARCHAR` and :class:`_types.NVARCHAR` datatypes, to indicate "maximum length possible". The dialect currently handles this as a length of "None" in the base type, rather than supplying a dialect-specific version of these types, so that a base type specified such as ``VARCHAR(None)`` can assume "unlengthed" behavior on more than one backend without using dialect-specific types. To build a SQL Server VARCHAR or NVARCHAR with MAX length, use None:: my_table = Table( 'my_table', metadata, Column('my_data', VARCHAR(None)), Column('my_n_data', NVARCHAR(None)) ) Collation Support ----------------- Character collations are supported by the base string types, specified by the string argument "collation":: from sqlalchemy import VARCHAR Column('login', VARCHAR(32, collation='Latin1_General_CI_AS')) When such a column is associated with a :class:`_schema.Table`, the CREATE TABLE statement for this column will yield:: login VARCHAR(32) COLLATE Latin1_General_CI_AS NULL LIMIT/OFFSET Support -------------------- MSSQL has added support for LIMIT / OFFSET as of SQL Server 2012, via the "OFFSET n ROWS" and "FETCH NEXT n ROWS" clauses. SQLAlchemy supports these syntaxes automatically if SQL Server 2012 or greater is detected. .. versionchanged:: 1.4 support added for SQL Server "OFFSET n ROWS" and "FETCH NEXT n ROWS" syntax. For statements that specify only LIMIT and no OFFSET, all versions of SQL Server support the TOP keyword. This syntax is used for all SQL Server versions when no OFFSET clause is present. A statement such as:: select(some_table).limit(5) will render similarly to:: SELECT TOP 5 col1, col2.. FROM table For versions of SQL Server prior to SQL Server 2012, a statement that uses LIMIT and OFFSET, or just OFFSET alone, will be rendered using the ``ROW_NUMBER()`` window function. A statement such as:: select(some_table).order_by(some_table.c.col3).limit(5).offset(10) will render similarly to:: SELECT anon_1.col1, anon_1.col2 FROM (SELECT col1, col2, ROW_NUMBER() OVER (ORDER BY col3) AS mssql_rn FROM table WHERE t.x = :x_1) AS anon_1 WHERE mssql_rn > :param_1 AND mssql_rn <= :param_2 + :param_1 Note that when using LIMIT and/or OFFSET, whether using the older or newer SQL Server syntaxes, the statement must have an ORDER BY as well, else a :class:`.CompileError` is raised. .. _mssql_comment_support: DDL Comment Support -------------------- Comment support, which includes DDL rendering for attributes such as :paramref:`_schema.Table.comment` and :paramref:`_schema.Column.comment`, as well as the ability to reflect these comments, is supported assuming a supported version of SQL Server is in use. If a non-supported version such as Azure Synapse is detected at first-connect time (based on the presence of the ``fn_listextendedproperty`` SQL function), comment support including rendering and table-comment reflection is disabled, as both features rely upon SQL Server stored procedures and functions that are not available on all backend types. To force comment support to be on or off, bypassing autodetection, set the parameter ``supports_comments`` within :func:`_sa.create_engine`:: e = create_engine("mssql+pyodbc://u:p@dsn", supports_comments=False) .. versionadded:: 2.0 Added support for table and column comments for the SQL Server dialect, including DDL generation and reflection. .. _mssql_isolation_level: Transaction Isolation Level --------------------------- All SQL Server dialects support setting of transaction isolation level both via a dialect-specific parameter :paramref:`_sa.create_engine.isolation_level` accepted by :func:`_sa.create_engine`, as well as the :paramref:`.Connection.execution_options.isolation_level` argument as passed to :meth:`_engine.Connection.execution_options`. This feature works by issuing the command ``SET TRANSACTION ISOLATION LEVEL `` for each new connection. To set isolation level using :func:`_sa.create_engine`:: engine = create_engine( "mssql+pyodbc://scott:tiger@ms_2008", isolation_level="REPEATABLE READ" ) To set using per-connection execution options:: connection = engine.connect() connection = connection.execution_options( isolation_level="READ COMMITTED" ) Valid values for ``isolation_level`` include: * ``AUTOCOMMIT`` - pyodbc / pymssql-specific * ``READ COMMITTED`` * ``READ UNCOMMITTED`` * ``REPEATABLE READ`` * ``SERIALIZABLE`` * ``SNAPSHOT`` - specific to SQL Server There are also more options for isolation level configurations, such as "sub-engine" objects linked to a main :class:`_engine.Engine` which each apply different isolation level settings. See the discussion at :ref:`dbapi_autocommit` for background. .. seealso:: :ref:`dbapi_autocommit` .. _mssql_reset_on_return: Temporary Table / Resource Reset for Connection Pooling ------------------------------------------------------- The :class:`.QueuePool` connection pool implementation used by the SQLAlchemy :class:`.Engine` object includes :ref:`reset on return ` behavior that will invoke the DBAPI ``.rollback()`` method when connections are returned to the pool. While this rollback will clear out the immediate state used by the previous transaction, it does not cover a wider range of session-level state, including temporary tables as well as other server state such as prepared statement handles and statement caches. An undocumented SQL Server procedure known as ``sp_reset_connection`` is known to be a workaround for this issue which will reset most of the session state that builds up on a connection, including temporary tables. To install ``sp_reset_connection`` as the means of performing reset-on-return, the :meth:`.PoolEvents.reset` event hook may be used, as demonstrated in the example below. The :paramref:`_sa.create_engine.pool_reset_on_return` parameter is set to ``None`` so that the custom scheme can replace the default behavior completely. The custom hook implementation calls ``.rollback()`` in any case, as it's usually important that the DBAPI's own tracking of commit/rollback will remain consistent with the state of the transaction:: from sqlalchemy import create_engine from sqlalchemy import event mssql_engine = create_engine( "mssql+pyodbc://scott:tiger^5HHH@mssql2017:1433/test?driver=ODBC+Driver+17+for+SQL+Server", # disable default reset-on-return scheme pool_reset_on_return=None, ) @event.listens_for(mssql_engine, "reset") def _reset_mssql(dbapi_connection, connection_record, reset_state): if not reset_state.terminate_only: dbapi_connection.execute("{call sys.sp_reset_connection}") # so that the DBAPI itself knows that the connection has been # reset dbapi_connection.rollback() .. versionchanged:: 2.0.0b3 Added additional state arguments to the :meth:`.PoolEvents.reset` event and additionally ensured the event is invoked for all "reset" occurrences, so that it's appropriate as a place for custom "reset" handlers. Previous schemes which use the :meth:`.PoolEvents.checkin` handler remain usable as well. .. seealso:: :ref:`pool_reset_on_return` - in the :ref:`pooling_toplevel` documentation Nullability ----------- MSSQL has support for three levels of column nullability. The default nullability allows nulls and is explicit in the CREATE TABLE construct:: name VARCHAR(20) NULL If ``nullable=None`` is specified then no specification is made. In other words the database's configured default is used. This will render:: name VARCHAR(20) If ``nullable`` is ``True`` or ``False`` then the column will be ``NULL`` or ``NOT NULL`` respectively. Date / Time Handling -------------------- DATE and TIME are supported. Bind parameters are converted to datetime.datetime() objects as required by most MSSQL drivers, and results are processed from strings if needed. The DATE and TIME types are not available for MSSQL 2005 and previous - if a server version below 2008 is detected, DDL for these types will be issued as DATETIME. .. _mssql_large_type_deprecation: Large Text/Binary Type Deprecation ---------------------------------- Per `SQL Server 2012/2014 Documentation `_, the ``NTEXT``, ``TEXT`` and ``IMAGE`` datatypes are to be removed from SQL Server in a future release. SQLAlchemy normally relates these types to the :class:`.UnicodeText`, :class:`_expression.TextClause` and :class:`.LargeBinary` datatypes. In order to accommodate this change, a new flag ``deprecate_large_types`` is added to the dialect, which will be automatically set based on detection of the server version in use, if not otherwise set by the user. The behavior of this flag is as follows: * When this flag is ``True``, the :class:`.UnicodeText`, :class:`_expression.TextClause` and :class:`.LargeBinary` datatypes, when used to render DDL, will render the types ``NVARCHAR(max)``, ``VARCHAR(max)``, and ``VARBINARY(max)``, respectively. This is a new behavior as of the addition of this flag. * When this flag is ``False``, the :class:`.UnicodeText`, :class:`_expression.TextClause` and :class:`.LargeBinary` datatypes, when used to render DDL, will render the types ``NTEXT``, ``TEXT``, and ``IMAGE``, respectively. This is the long-standing behavior of these types. * The flag begins with the value ``None``, before a database connection is established. If the dialect is used to render DDL without the flag being set, it is interpreted the same as ``False``. * On first connection, the dialect detects if SQL Server version 2012 or greater is in use; if the flag is still at ``None``, it sets it to ``True`` or ``False`` based on whether 2012 or greater is detected. * The flag can be set to either ``True`` or ``False`` when the dialect is created, typically via :func:`_sa.create_engine`:: eng = create_engine("mssql+pymssql://user:pass@host/db", deprecate_large_types=True) * Complete control over whether the "old" or "new" types are rendered is available in all SQLAlchemy versions by using the UPPERCASE type objects instead: :class:`_types.NVARCHAR`, :class:`_types.VARCHAR`, :class:`_types.VARBINARY`, :class:`_types.TEXT`, :class:`_mssql.NTEXT`, :class:`_mssql.IMAGE` will always remain fixed and always output exactly that type. .. _multipart_schema_names: Multipart Schema Names ---------------------- SQL Server schemas sometimes require multiple parts to their "schema" qualifier, that is, including the database name and owner name as separate tokens, such as ``mydatabase.dbo.some_table``. These multipart names can be set at once using the :paramref:`_schema.Table.schema` argument of :class:`_schema.Table`:: Table( "some_table", metadata, Column("q", String(50)), schema="mydatabase.dbo" ) When performing operations such as table or component reflection, a schema argument that contains a dot will be split into separate "database" and "owner" components in order to correctly query the SQL Server information schema tables, as these two values are stored separately. Additionally, when rendering the schema name for DDL or SQL, the two components will be quoted separately for case sensitive names and other special characters. Given an argument as below:: Table( "some_table", metadata, Column("q", String(50)), schema="MyDataBase.dbo" ) The above schema would be rendered as ``[MyDataBase].dbo``, and also in reflection, would be reflected using "dbo" as the owner and "MyDataBase" as the database name. To control how the schema name is broken into database / owner, specify brackets (which in SQL Server are quoting characters) in the name. Below, the "owner" will be considered as ``MyDataBase.dbo`` and the "database" will be None:: Table( "some_table", metadata, Column("q", String(50)), schema="[MyDataBase.dbo]" ) To individually specify both database and owner name with special characters or embedded dots, use two sets of brackets:: Table( "some_table", metadata, Column("q", String(50)), schema="[MyDataBase.Period].[MyOwner.Dot]" ) .. versionchanged:: 1.2 the SQL Server dialect now treats brackets as identifier delimiters splitting the schema into separate database and owner tokens, to allow dots within either name itself. .. _legacy_schema_rendering: Legacy Schema Mode ------------------ Very old versions of the MSSQL dialect introduced the behavior such that a schema-qualified table would be auto-aliased when used in a SELECT statement; given a table:: account_table = Table( 'account', metadata, Column('id', Integer, primary_key=True), Column('info', String(100)), schema="customer_schema" ) this legacy mode of rendering would assume that "customer_schema.account" would not be accepted by all parts of the SQL statement, as illustrated below: .. sourcecode:: pycon+sql >>> eng = create_engine("mssql+pymssql://mydsn", legacy_schema_aliasing=True) >>> print(account_table.select().compile(eng)) {printsql}SELECT account_1.id, account_1.info FROM customer_schema.account AS account_1 This mode of behavior is now off by default, as it appears to have served no purpose; however in the case that legacy applications rely upon it, it is available using the ``legacy_schema_aliasing`` argument to :func:`_sa.create_engine` as illustrated above. .. deprecated:: 1.4 The ``legacy_schema_aliasing`` flag is now deprecated and will be removed in a future release. .. _mssql_indexes: Clustered Index Support ----------------------- The MSSQL dialect supports clustered indexes (and primary keys) via the ``mssql_clustered`` option. This option is available to :class:`.Index`, :class:`.UniqueConstraint`. and :class:`.PrimaryKeyConstraint`. For indexes this option can be combined with the ``mssql_columnstore`` one to create a clustered columnstore index. To generate a clustered index:: Index("my_index", table.c.x, mssql_clustered=True) which renders the index as ``CREATE CLUSTERED INDEX my_index ON table (x)``. To generate a clustered primary key use:: Table('my_table', metadata, Column('x', ...), Column('y', ...), PrimaryKeyConstraint("x", "y", mssql_clustered=True)) which will render the table, for example, as:: CREATE TABLE my_table (x INTEGER NOT NULL, y INTEGER NOT NULL, PRIMARY KEY CLUSTERED (x, y)) Similarly, we can generate a clustered unique constraint using:: Table('my_table', metadata, Column('x', ...), Column('y', ...), PrimaryKeyConstraint("x"), UniqueConstraint("y", mssql_clustered=True), ) To explicitly request a non-clustered primary key (for example, when a separate clustered index is desired), use:: Table('my_table', metadata, Column('x', ...), Column('y', ...), PrimaryKeyConstraint("x", "y", mssql_clustered=False)) which will render the table, for example, as:: CREATE TABLE my_table (x INTEGER NOT NULL, y INTEGER NOT NULL, PRIMARY KEY NONCLUSTERED (x, y)) Columnstore Index Support ------------------------- The MSSQL dialect supports columnstore indexes via the ``mssql_columnstore`` option. This option is available to :class:`.Index`. It be combined with the ``mssql_clustered`` option to create a clustered columnstore index. To generate a columnstore index:: Index("my_index", table.c.x, mssql_columnstore=True) which renders the index as ``CREATE COLUMNSTORE INDEX my_index ON table (x)``. To generate a clustered columnstore index provide no columns:: idx = Index("my_index", mssql_clustered=True, mssql_columnstore=True) # required to associate the index with the table table.append_constraint(idx) the above renders the index as ``CREATE CLUSTERED COLUMNSTORE INDEX my_index ON table``. .. versionadded:: 2.0.18 MSSQL-Specific Index Options ----------------------------- In addition to clustering, the MSSQL dialect supports other special options for :class:`.Index`. INCLUDE ^^^^^^^ The ``mssql_include`` option renders INCLUDE(colname) for the given string names:: Index("my_index", table.c.x, mssql_include=['y']) would render the index as ``CREATE INDEX my_index ON table (x) INCLUDE (y)`` .. _mssql_index_where: Filtered Indexes ^^^^^^^^^^^^^^^^ The ``mssql_where`` option renders WHERE(condition) for the given string names:: Index("my_index", table.c.x, mssql_where=table.c.x > 10) would render the index as ``CREATE INDEX my_index ON table (x) WHERE x > 10``. .. versionadded:: 1.3.4 Index ordering ^^^^^^^^^^^^^^ Index ordering is available via functional expressions, such as:: Index("my_index", table.c.x.desc()) would render the index as ``CREATE INDEX my_index ON table (x DESC)`` .. seealso:: :ref:`schema_indexes_functional` Compatibility Levels -------------------- MSSQL supports the notion of setting compatibility levels at the database level. This allows, for instance, to run a database that is compatible with SQL2000 while running on a SQL2005 database server. ``server_version_info`` will always return the database server version information (in this case SQL2005) and not the compatibility level information. Because of this, if running under a backwards compatibility mode SQLAlchemy may attempt to use T-SQL statements that are unable to be parsed by the database server. .. _mssql_triggers: Triggers -------- SQLAlchemy by default uses OUTPUT INSERTED to get at newly generated primary key values via IDENTITY columns or other server side defaults. MS-SQL does not allow the usage of OUTPUT INSERTED on tables that have triggers. To disable the usage of OUTPUT INSERTED on a per-table basis, specify ``implicit_returning=False`` for each :class:`_schema.Table` which has triggers:: Table('mytable', metadata, Column('id', Integer, primary_key=True), # ..., implicit_returning=False ) Declarative form:: class MyClass(Base): # ... __table_args__ = {'implicit_returning':False} .. _mssql_rowcount_versioning: Rowcount Support / ORM Versioning --------------------------------- The SQL Server drivers may have limited ability to return the number of rows updated from an UPDATE or DELETE statement. As of this writing, the PyODBC driver is not able to return a rowcount when OUTPUT INSERTED is used. Previous versions of SQLAlchemy therefore had limitations for features such as the "ORM Versioning" feature that relies upon accurate rowcounts in order to match version numbers with matched rows. SQLAlchemy 2.0 now retrieves the "rowcount" manually for these particular use cases based on counting the rows that arrived back within RETURNING; so while the driver still has this limitation, the ORM Versioning feature is no longer impacted by it. As of SQLAlchemy 2.0.5, ORM versioning has been fully re-enabled for the pyodbc driver. .. versionchanged:: 2.0.5 ORM versioning support is restored for the pyodbc driver. Previously, a warning would be emitted during ORM flush that versioning was not supported. Enabling Snapshot Isolation --------------------------- SQL Server has a default transaction isolation mode that locks entire tables, and causes even mildly concurrent applications to have long held locks and frequent deadlocks. Enabling snapshot isolation for the database as a whole is recommended for modern levels of concurrency support. This is accomplished via the following ALTER DATABASE commands executed at the SQL prompt:: ALTER DATABASE MyDatabase SET ALLOW_SNAPSHOT_ISOLATION ON ALTER DATABASE MyDatabase SET READ_COMMITTED_SNAPSHOT ON Background on SQL Server snapshot isolation is available at https://msdn.microsoft.com/en-us/library/ms175095.aspx. """ # noqa from __future__ import annotations import codecs import datetime import operator import re from typing import overload from typing import TYPE_CHECKING from uuid import UUID as _python_UUID from . import information_schema as ischema from .json import JSON from .json import JSONIndexType from .json import JSONPathType from ... import exc from ... import Identity from ... import schema as sa_schema from ... import Sequence from ... import sql from ... import text from ... import util from ...engine import cursor as _cursor from ...engine import default from ...engine import reflection from ...engine.reflection import ReflectionDefaults from ...sql import coercions from ...sql import compiler from ...sql import elements from ...sql import expression from ...sql import func from ...sql import quoted_name from ...sql import roles from ...sql import sqltypes from ...sql import try_cast as try_cast # noqa: F401 from ...sql import util as sql_util from ...sql._typing import is_sql_compiler from ...sql.compiler import InsertmanyvaluesSentinelOpts from ...sql.elements import TryCast as TryCast # noqa: F401 from ...types import BIGINT from ...types import BINARY from ...types import CHAR from ...types import DATE from ...types import DATETIME from ...types import DECIMAL from ...types import FLOAT from ...types import INTEGER from ...types import NCHAR from ...types import NUMERIC from ...types import NVARCHAR from ...types import SMALLINT from ...types import TEXT from ...types import VARCHAR from ...util import update_wrapper from ...util.typing import Literal if TYPE_CHECKING: from ...sql.dml import DMLState from ...sql.selectable import TableClause # https://sqlserverbuilds.blogspot.com/ MS_2017_VERSION = (14,) MS_2016_VERSION = (13,) MS_2014_VERSION = (12,) MS_2012_VERSION = (11,) MS_2008_VERSION = (10,) MS_2005_VERSION = (9,) MS_2000_VERSION = (8,) RESERVED_WORDS = { "add", "all", "alter", "and", "any", "as", "asc", "authorization", "backup", "begin", "between", "break", "browse", "bulk", "by", "cascade", "case", "check", "checkpoint", "close", "clustered", "coalesce", "collate", "column", "commit", "compute", "constraint", "contains", "containstable", "continue", "convert", "create", "cross", "current", "current_date", "current_time", "current_timestamp", "current_user", "cursor", "database", "dbcc", "deallocate", "declare", "default", "delete", "deny", "desc", "disk", "distinct", "distributed", "double", "drop", "dump", "else", "end", "errlvl", "escape", "except", "exec", "execute", "exists", "exit", "external", "fetch", "file", "fillfactor", "for", "foreign", "freetext", "freetexttable", "from", "full", "function", "goto", "grant", "group", "having", "holdlock", "identity", "identity_insert", "identitycol", "if", "in", "index", "inner", "insert", "intersect", "into", "is", "join", "key", "kill", "left", "like", "lineno", "load", "merge", "national", "nocheck", "nonclustered", "not", "null", "nullif", "of", "off", "offsets", "on", "open", "opendatasource", "openquery", "openrowset", "openxml", "option", "or", "order", "outer", "over", "percent", "pivot", "plan", "precision", "primary", "print", "proc", "procedure", "public", "raiserror", "read", "readtext", "reconfigure", "references", "replication", "restore", "restrict", "return", "revert", "revoke", "right", "rollback", "rowcount", "rowguidcol", "rule", "save", "schema", "securityaudit", "select", "session_user", "set", "setuser", "shutdown", "some", "statistics", "system_user", "table", "tablesample", "textsize", "then", "to", "top", "tran", "transaction", "trigger", "truncate", "tsequal", "union", "unique", "unpivot", "update", "updatetext", "use", "user", "values", "varying", "view", "waitfor", "when", "where", "while", "with", "writetext", } class REAL(sqltypes.REAL): """the SQL Server REAL datatype.""" def __init__(self, **kw): # REAL is a synonym for FLOAT(24) on SQL server. # it is only accepted as the word "REAL" in DDL, the numeric # precision value is not allowed to be present kw.setdefault("precision", 24) super().__init__(**kw) class DOUBLE_PRECISION(sqltypes.DOUBLE_PRECISION): """the SQL Server DOUBLE PRECISION datatype. .. versionadded:: 2.0.11 """ def __init__(self, **kw): # DOUBLE PRECISION is a synonym for FLOAT(53) on SQL server. # it is only accepted as the word "DOUBLE PRECISION" in DDL, # the numeric precision value is not allowed to be present kw.setdefault("precision", 53) super().__init__(**kw) class TINYINT(sqltypes.Integer): __visit_name__ = "TINYINT" # MSSQL DATE/TIME types have varied behavior, sometimes returning # strings. MSDate/TIME check for everything, and always # filter bind parameters into datetime objects (required by pyodbc, # not sure about other dialects). class _MSDate(sqltypes.Date): def bind_processor(self, dialect): def process(value): if type(value) == datetime.date: return datetime.datetime(value.year, value.month, value.day) else: return value return process _reg = re.compile(r"(\d+)-(\d+)-(\d+)") def result_processor(self, dialect, coltype): def process(value): if isinstance(value, datetime.datetime): return value.date() elif isinstance(value, str): m = self._reg.match(value) if not m: raise ValueError( "could not parse %r as a date value" % (value,) ) return datetime.date(*[int(x or 0) for x in m.groups()]) else: return value return process class TIME(sqltypes.TIME): def __init__(self, precision=None, **kwargs): self.precision = precision super().__init__() __zero_date = datetime.date(1900, 1, 1) def bind_processor(self, dialect): def process(value): if isinstance(value, datetime.datetime): value = datetime.datetime.combine( self.__zero_date, value.time() ) elif isinstance(value, datetime.time): """issue #5339 per: https://github.com/mkleehammer/pyodbc/wiki/Tips-and-Tricks-by-Database-Platform#time-columns pass TIME value as string """ # noqa value = str(value) return value return process _reg = re.compile(r"(\d+):(\d+):(\d+)(?:\.(\d{0,6}))?") def result_processor(self, dialect, coltype): def process(value): if isinstance(value, datetime.datetime): return value.time() elif isinstance(value, str): m = self._reg.match(value) if not m: raise ValueError( "could not parse %r as a time value" % (value,) ) return datetime.time(*[int(x or 0) for x in m.groups()]) else: return value return process _MSTime = TIME class _BASETIMEIMPL(TIME): __visit_name__ = "_BASETIMEIMPL" class _DateTimeBase: def bind_processor(self, dialect): def process(value): if type(value) == datetime.date: return datetime.datetime(value.year, value.month, value.day) else: return value return process class _MSDateTime(_DateTimeBase, sqltypes.DateTime): pass class SMALLDATETIME(_DateTimeBase, sqltypes.DateTime): __visit_name__ = "SMALLDATETIME" class DATETIME2(_DateTimeBase, sqltypes.DateTime): __visit_name__ = "DATETIME2" def __init__(self, precision=None, **kw): super().__init__(**kw) self.precision = precision class DATETIMEOFFSET(_DateTimeBase, sqltypes.DateTime): __visit_name__ = "DATETIMEOFFSET" def __init__(self, precision=None, **kw): super().__init__(**kw) self.precision = precision class _UnicodeLiteral: def literal_processor(self, dialect): def process(value): value = value.replace("'", "''") if dialect.identifier_preparer._double_percents: value = value.replace("%", "%%") return "N'%s'" % value return process class _MSUnicode(_UnicodeLiteral, sqltypes.Unicode): pass class _MSUnicodeText(_UnicodeLiteral, sqltypes.UnicodeText): pass class TIMESTAMP(sqltypes._Binary): """Implement the SQL Server TIMESTAMP type. Note this is **completely different** than the SQL Standard TIMESTAMP type, which is not supported by SQL Server. It is a read-only datatype that does not support INSERT of values. .. versionadded:: 1.2 .. seealso:: :class:`_mssql.ROWVERSION` """ __visit_name__ = "TIMESTAMP" # expected by _Binary to be present length = None def __init__(self, convert_int=False): """Construct a TIMESTAMP or ROWVERSION type. :param convert_int: if True, binary integer values will be converted to integers on read. .. versionadded:: 1.2 """ self.convert_int = convert_int def result_processor(self, dialect, coltype): super_ = super().result_processor(dialect, coltype) if self.convert_int: def process(value): if super_: value = super_(value) if value is not None: # https://stackoverflow.com/a/30403242/34549 value = int(codecs.encode(value, "hex"), 16) return value return process else: return super_ class ROWVERSION(TIMESTAMP): """Implement the SQL Server ROWVERSION type. The ROWVERSION datatype is a SQL Server synonym for the TIMESTAMP datatype, however current SQL Server documentation suggests using ROWVERSION for new datatypes going forward. The ROWVERSION datatype does **not** reflect (e.g. introspect) from the database as itself; the returned datatype will be :class:`_mssql.TIMESTAMP`. This is a read-only datatype that does not support INSERT of values. .. versionadded:: 1.2 .. seealso:: :class:`_mssql.TIMESTAMP` """ __visit_name__ = "ROWVERSION" class NTEXT(sqltypes.UnicodeText): """MSSQL NTEXT type, for variable-length unicode text up to 2^30 characters.""" __visit_name__ = "NTEXT" class VARBINARY(sqltypes.VARBINARY, sqltypes.LargeBinary): """The MSSQL VARBINARY type. This type adds additional features to the core :class:`_types.VARBINARY` type, including "deprecate_large_types" mode where either ``VARBINARY(max)`` or IMAGE is rendered, as well as the SQL Server ``FILESTREAM`` option. .. seealso:: :ref:`mssql_large_type_deprecation` """ __visit_name__ = "VARBINARY" def __init__(self, length=None, filestream=False): """ Construct a VARBINARY type. :param length: optional, a length for the column for use in DDL statements, for those binary types that accept a length, such as the MySQL BLOB type. :param filestream=False: if True, renders the ``FILESTREAM`` keyword in the table definition. In this case ``length`` must be ``None`` or ``'max'``. .. versionadded:: 1.4.31 """ self.filestream = filestream if self.filestream and length not in (None, "max"): raise ValueError( "length must be None or 'max' when setting filestream" ) super().__init__(length=length) class IMAGE(sqltypes.LargeBinary): __visit_name__ = "IMAGE" class XML(sqltypes.Text): """MSSQL XML type. This is a placeholder type for reflection purposes that does not include any Python-side datatype support. It also does not currently support additional arguments, such as "CONTENT", "DOCUMENT", "xml_schema_collection". """ __visit_name__ = "XML" class BIT(sqltypes.Boolean): """MSSQL BIT type. Both pyodbc and pymssql return values from BIT columns as Python so just subclass Boolean. """ __visit_name__ = "BIT" class MONEY(sqltypes.TypeEngine): __visit_name__ = "MONEY" class SMALLMONEY(sqltypes.TypeEngine): __visit_name__ = "SMALLMONEY" class MSUUid(sqltypes.Uuid): def bind_processor(self, dialect): if self.native_uuid: # this is currently assuming pyodbc; might not work for # some other mssql driver return None else: if self.as_uuid: def process(value): if value is not None: value = value.hex return value return process else: def process(value): if value is not None: value = value.replace("-", "").replace("''", "'") return value return process def literal_processor(self, dialect): if self.native_uuid: def process(value): return f"""'{str(value).replace("''", "'")}'""" return process else: if self.as_uuid: def process(value): return f"""'{value.hex}'""" return process else: def process(value): return f"""'{ value.replace("-", "").replace("'", "''") }'""" return process class UNIQUEIDENTIFIER(sqltypes.Uuid[sqltypes._UUID_RETURN]): __visit_name__ = "UNIQUEIDENTIFIER" @overload def __init__( self: UNIQUEIDENTIFIER[_python_UUID], as_uuid: Literal[True] = ... ): ... @overload def __init__( self: UNIQUEIDENTIFIER[str], as_uuid: Literal[False] = ... ): ... def __init__(self, as_uuid: bool = True): """Construct a :class:`_mssql.UNIQUEIDENTIFIER` type. :param as_uuid=True: if True, values will be interpreted as Python uuid objects, converting to/from string via the DBAPI. .. versionchanged: 2.0 Added direct "uuid" support to the :class:`_mssql.UNIQUEIDENTIFIER` datatype; uuid interpretation defaults to ``True``. """ self.as_uuid = as_uuid self.native_uuid = True class SQL_VARIANT(sqltypes.TypeEngine): __visit_name__ = "SQL_VARIANT" # old names. MSDateTime = _MSDateTime MSDate = _MSDate MSReal = REAL MSTinyInteger = TINYINT MSTime = TIME MSSmallDateTime = SMALLDATETIME MSDateTime2 = DATETIME2 MSDateTimeOffset = DATETIMEOFFSET MSText = TEXT MSNText = NTEXT MSString = VARCHAR MSNVarchar = NVARCHAR MSChar = CHAR MSNChar = NCHAR MSBinary = BINARY MSVarBinary = VARBINARY MSImage = IMAGE MSBit = BIT MSMoney = MONEY MSSmallMoney = SMALLMONEY MSUniqueIdentifier = UNIQUEIDENTIFIER MSVariant = SQL_VARIANT ischema_names = { "int": INTEGER, "bigint": BIGINT, "smallint": SMALLINT, "tinyint": TINYINT, "varchar": VARCHAR, "nvarchar": NVARCHAR, "char": CHAR, "nchar": NCHAR, "text": TEXT, "ntext": NTEXT, "decimal": DECIMAL, "numeric": NUMERIC, "float": FLOAT, "datetime": DATETIME, "datetime2": DATETIME2, "datetimeoffset": DATETIMEOFFSET, "date": DATE, "time": TIME, "smalldatetime": SMALLDATETIME, "binary": BINARY, "varbinary": VARBINARY, "bit": BIT, "real": REAL, "double precision": DOUBLE_PRECISION, "image": IMAGE, "xml": XML, "timestamp": TIMESTAMP, "money": MONEY, "smallmoney": SMALLMONEY, "uniqueidentifier": UNIQUEIDENTIFIER, "sql_variant": SQL_VARIANT, } class MSTypeCompiler(compiler.GenericTypeCompiler): def _extend(self, spec, type_, length=None): """Extend a string-type declaration with standard SQL COLLATE annotations. """ if getattr(type_, "collation", None): collation = "COLLATE %s" % type_.collation else: collation = None if not length: length = type_.length if length: spec = spec + "(%s)" % length return " ".join([c for c in (spec, collation) if c is not None]) def visit_double(self, type_, **kw): return self.visit_DOUBLE_PRECISION(type_, **kw) def visit_FLOAT(self, type_, **kw): precision = getattr(type_, "precision", None) if precision is None: return "FLOAT" else: return "FLOAT(%(precision)s)" % {"precision": precision} def visit_TINYINT(self, type_, **kw): return "TINYINT" def visit_TIME(self, type_, **kw): precision = getattr(type_, "precision", None) if precision is not None: return "TIME(%s)" % precision else: return "TIME" def visit_TIMESTAMP(self, type_, **kw): return "TIMESTAMP" def visit_ROWVERSION(self, type_, **kw): return "ROWVERSION" def visit_datetime(self, type_, **kw): if type_.timezone: return self.visit_DATETIMEOFFSET(type_, **kw) else: return self.visit_DATETIME(type_, **kw) def visit_DATETIMEOFFSET(self, type_, **kw): precision = getattr(type_, "precision", None) if precision is not None: return "DATETIMEOFFSET(%s)" % type_.precision else: return "DATETIMEOFFSET" def visit_DATETIME2(self, type_, **kw): precision = getattr(type_, "precision", None) if precision is not None: return "DATETIME2(%s)" % precision else: return "DATETIME2" def visit_SMALLDATETIME(self, type_, **kw): return "SMALLDATETIME" def visit_unicode(self, type_, **kw): return self.visit_NVARCHAR(type_, **kw) def visit_text(self, type_, **kw): if self.dialect.deprecate_large_types: return self.visit_VARCHAR(type_, **kw) else: return self.visit_TEXT(type_, **kw) def visit_unicode_text(self, type_, **kw): if self.dialect.deprecate_large_types: return self.visit_NVARCHAR(type_, **kw) else: return self.visit_NTEXT(type_, **kw) def visit_NTEXT(self, type_, **kw): return self._extend("NTEXT", type_) def visit_TEXT(self, type_, **kw): return self._extend("TEXT", type_) def visit_VARCHAR(self, type_, **kw): return self._extend("VARCHAR", type_, length=type_.length or "max") def visit_CHAR(self, type_, **kw): return self._extend("CHAR", type_) def visit_NCHAR(self, type_, **kw): return self._extend("NCHAR", type_) def visit_NVARCHAR(self, type_, **kw): return self._extend("NVARCHAR", type_, length=type_.length or "max") def visit_date(self, type_, **kw): if self.dialect.server_version_info < MS_2008_VERSION: return self.visit_DATETIME(type_, **kw) else: return self.visit_DATE(type_, **kw) def visit__BASETIMEIMPL(self, type_, **kw): return self.visit_time(type_, **kw) def visit_time(self, type_, **kw): if self.dialect.server_version_info < MS_2008_VERSION: return self.visit_DATETIME(type_, **kw) else: return self.visit_TIME(type_, **kw) def visit_large_binary(self, type_, **kw): if self.dialect.deprecate_large_types: return self.visit_VARBINARY(type_, **kw) else: return self.visit_IMAGE(type_, **kw) def visit_IMAGE(self, type_, **kw): return "IMAGE" def visit_XML(self, type_, **kw): return "XML" def visit_VARBINARY(self, type_, **kw): text = self._extend("VARBINARY", type_, length=type_.length or "max") if getattr(type_, "filestream", False): text += " FILESTREAM" return text def visit_boolean(self, type_, **kw): return self.visit_BIT(type_) def visit_BIT(self, type_, **kw): return "BIT" def visit_JSON(self, type_, **kw): # this is a bit of a break with SQLAlchemy's convention of # "UPPERCASE name goes to UPPERCASE type name with no modification" return self._extend("NVARCHAR", type_, length="max") def visit_MONEY(self, type_, **kw): return "MONEY" def visit_SMALLMONEY(self, type_, **kw): return "SMALLMONEY" def visit_uuid(self, type_, **kw): if type_.native_uuid: return self.visit_UNIQUEIDENTIFIER(type_, **kw) else: return super().visit_uuid(type_, **kw) def visit_UNIQUEIDENTIFIER(self, type_, **kw): return "UNIQUEIDENTIFIER" def visit_SQL_VARIANT(self, type_, **kw): return "SQL_VARIANT" class MSExecutionContext(default.DefaultExecutionContext): _enable_identity_insert = False _select_lastrowid = False _lastrowid = None dialect: MSDialect def _opt_encode(self, statement): if self.compiled and self.compiled.schema_translate_map: rst = self.compiled.preparer._render_schema_translates statement = rst(statement, self.compiled.schema_translate_map) return statement def pre_exec(self): """Activate IDENTITY_INSERT if needed.""" if self.isinsert: if TYPE_CHECKING: assert is_sql_compiler(self.compiled) assert isinstance(self.compiled.compile_state, DMLState) assert isinstance( self.compiled.compile_state.dml_table, TableClause ) tbl = self.compiled.compile_state.dml_table id_column = tbl._autoincrement_column if id_column is not None and ( not isinstance(id_column.default, Sequence) ): insert_has_identity = True compile_state = self.compiled.dml_compile_state self._enable_identity_insert = ( id_column.key in self.compiled_parameters[0] ) or ( compile_state._dict_parameters and (id_column.key in compile_state._insert_col_keys) ) else: insert_has_identity = False self._enable_identity_insert = False self._select_lastrowid = ( not self.compiled.inline and insert_has_identity and not self.compiled.effective_returning and not self._enable_identity_insert and not self.executemany ) if self._enable_identity_insert: self.root_connection._cursor_execute( self.cursor, self._opt_encode( "SET IDENTITY_INSERT %s ON" % self.identifier_preparer.format_table(tbl) ), (), self, ) def post_exec(self): """Disable IDENTITY_INSERT if enabled.""" conn = self.root_connection if self.isinsert or self.isupdate or self.isdelete: self._rowcount = self.cursor.rowcount if self._select_lastrowid: if self.dialect.use_scope_identity: conn._cursor_execute( self.cursor, "SELECT scope_identity() AS lastrowid", (), self, ) else: conn._cursor_execute( self.cursor, "SELECT @@identity AS lastrowid", (), self ) # fetchall() ensures the cursor is consumed without closing it row = self.cursor.fetchall()[0] self._lastrowid = int(row[0]) self.cursor_fetch_strategy = _cursor._NO_CURSOR_DML elif ( self.compiled is not None and is_sql_compiler(self.compiled) and self.compiled.effective_returning ): self.cursor_fetch_strategy = ( _cursor.FullyBufferedCursorFetchStrategy( self.cursor, self.cursor.description, self.cursor.fetchall(), ) ) if self._enable_identity_insert: if TYPE_CHECKING: assert is_sql_compiler(self.compiled) assert isinstance(self.compiled.compile_state, DMLState) assert isinstance( self.compiled.compile_state.dml_table, TableClause ) conn._cursor_execute( self.cursor, self._opt_encode( "SET IDENTITY_INSERT %s OFF" % self.identifier_preparer.format_table( self.compiled.compile_state.dml_table ) ), (), self, ) def get_lastrowid(self): return self._lastrowid def handle_dbapi_exception(self, e): if self._enable_identity_insert: try: self.cursor.execute( self._opt_encode( "SET IDENTITY_INSERT %s OFF" % self.identifier_preparer.format_table( self.compiled.compile_state.dml_table ) ) ) except Exception: pass def fire_sequence(self, seq, type_): return self._execute_scalar( ( "SELECT NEXT VALUE FOR %s" % self.identifier_preparer.format_sequence(seq) ), type_, ) def get_insert_default(self, column): if ( isinstance(column, sa_schema.Column) and column is column.table._autoincrement_column and isinstance(column.default, sa_schema.Sequence) and column.default.optional ): return None return super().get_insert_default(column) class MSSQLCompiler(compiler.SQLCompiler): returning_precedes_values = True extract_map = util.update_copy( compiler.SQLCompiler.extract_map, { "doy": "dayofyear", "dow": "weekday", "milliseconds": "millisecond", "microseconds": "microsecond", }, ) def __init__(self, *args, **kwargs): self.tablealiases = {} super().__init__(*args, **kwargs) def _with_legacy_schema_aliasing(fn): def decorate(self, *arg, **kw): if self.dialect.legacy_schema_aliasing: return fn(self, *arg, **kw) else: super_ = getattr(super(MSSQLCompiler, self), fn.__name__) return super_(*arg, **kw) return decorate def visit_now_func(self, fn, **kw): return "CURRENT_TIMESTAMP" def visit_current_date_func(self, fn, **kw): return "GETDATE()" def visit_length_func(self, fn, **kw): return "LEN%s" % self.function_argspec(fn, **kw) def visit_char_length_func(self, fn, **kw): return "LEN%s" % self.function_argspec(fn, **kw) def visit_aggregate_strings_func(self, fn, **kw): expr = fn.clauses.clauses[0]._compiler_dispatch(self, **kw) kw["literal_execute"] = True delimeter = fn.clauses.clauses[1]._compiler_dispatch(self, **kw) return f"string_agg({expr}, {delimeter})" def visit_concat_op_expression_clauselist( self, clauselist, operator, **kw ): return " + ".join(self.process(elem, **kw) for elem in clauselist) def visit_concat_op_binary(self, binary, operator, **kw): return "%s + %s" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) def visit_true(self, expr, **kw): return "1" def visit_false(self, expr, **kw): return "0" def visit_match_op_binary(self, binary, operator, **kw): return "CONTAINS (%s, %s)" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) def get_select_precolumns(self, select, **kw): """MS-SQL puts TOP, it's version of LIMIT here""" s = super().get_select_precolumns(select, **kw) if select._has_row_limiting_clause and self._use_top(select): # ODBC drivers and possibly others # don't support bind params in the SELECT clause on SQL Server. # so have to use literal here. kw["literal_execute"] = True s += "TOP %s " % self.process( self._get_limit_or_fetch(select), **kw ) if select._fetch_clause is not None: if select._fetch_clause_options["percent"]: s += "PERCENT " if select._fetch_clause_options["with_ties"]: s += "WITH TIES " return s def get_from_hint_text(self, table, text): return text def get_crud_hint_text(self, table, text): return text def _get_limit_or_fetch(self, select): if select._fetch_clause is None: return select._limit_clause else: return select._fetch_clause def _use_top(self, select): return (select._offset_clause is None) and ( select._simple_int_clause(select._limit_clause) or ( # limit can use TOP with is by itself. fetch only uses TOP # when it needs to because of PERCENT and/or WITH TIES # TODO: Why? shouldn't we use TOP always ? select._simple_int_clause(select._fetch_clause) and ( select._fetch_clause_options["percent"] or select._fetch_clause_options["with_ties"] ) ) ) def limit_clause(self, cs, **kwargs): return "" def _check_can_use_fetch_limit(self, select): # to use ROW_NUMBER(), an ORDER BY is required. # OFFSET are FETCH are options of the ORDER BY clause if not select._order_by_clause.clauses: raise exc.CompileError( "MSSQL requires an order_by when " "using an OFFSET or a non-simple " "LIMIT clause" ) if select._fetch_clause_options is not None and ( select._fetch_clause_options["percent"] or select._fetch_clause_options["with_ties"] ): raise exc.CompileError( "MSSQL needs TOP to use PERCENT and/or WITH TIES. " "Only simple fetch without offset can be used." ) def _row_limit_clause(self, select, **kw): """MSSQL 2012 supports OFFSET/FETCH operators Use it instead subquery with row_number """ if self.dialect._supports_offset_fetch and not self._use_top(select): self._check_can_use_fetch_limit(select) return self.fetch_clause( select, fetch_clause=self._get_limit_or_fetch(select), require_offset=True, **kw, ) else: return "" def visit_try_cast(self, element, **kw): return "TRY_CAST (%s AS %s)" % ( self.process(element.clause, **kw), self.process(element.typeclause, **kw), ) def translate_select_structure(self, select_stmt, **kwargs): """Look for ``LIMIT`` and OFFSET in a select statement, and if so tries to wrap it in a subquery with ``row_number()`` criterion. MSSQL 2012 and above are excluded """ select = select_stmt if ( select._has_row_limiting_clause and not self.dialect._supports_offset_fetch and not self._use_top(select) and not getattr(select, "_mssql_visit", None) ): self._check_can_use_fetch_limit(select) _order_by_clauses = [ sql_util.unwrap_label_reference(elem) for elem in select._order_by_clause.clauses ] limit_clause = self._get_limit_or_fetch(select) offset_clause = select._offset_clause select = select._generate() select._mssql_visit = True select = ( select.add_columns( sql.func.ROW_NUMBER() .over(order_by=_order_by_clauses) .label("mssql_rn") ) .order_by(None) .alias() ) mssql_rn = sql.column("mssql_rn") limitselect = sql.select( *[c for c in select.c if c.key != "mssql_rn"] ) if offset_clause is not None: limitselect = limitselect.where(mssql_rn > offset_clause) if limit_clause is not None: limitselect = limitselect.where( mssql_rn <= (limit_clause + offset_clause) ) else: limitselect = limitselect.where(mssql_rn <= (limit_clause)) return limitselect else: return select @_with_legacy_schema_aliasing def visit_table(self, table, mssql_aliased=False, iscrud=False, **kwargs): if mssql_aliased is table or iscrud: return super().visit_table(table, **kwargs) # alias schema-qualified tables alias = self._schema_aliased_table(table) if alias is not None: return self.process(alias, mssql_aliased=table, **kwargs) else: return super().visit_table(table, **kwargs) @_with_legacy_schema_aliasing def visit_alias(self, alias, **kw): # translate for schema-qualified table aliases kw["mssql_aliased"] = alias.element return super().visit_alias(alias, **kw) @_with_legacy_schema_aliasing def visit_column(self, column, add_to_result_map=None, **kw): if ( column.table is not None and (not self.isupdate and not self.isdelete) or self.is_subquery() ): # translate for schema-qualified table aliases t = self._schema_aliased_table(column.table) if t is not None: converted = elements._corresponding_column_or_error(t, column) if add_to_result_map is not None: add_to_result_map( column.name, column.name, (column, column.name, column.key), column.type, ) return super().visit_column(converted, **kw) return super().visit_column( column, add_to_result_map=add_to_result_map, **kw ) def _schema_aliased_table(self, table): if getattr(table, "schema", None) is not None: if table not in self.tablealiases: self.tablealiases[table] = table.alias() return self.tablealiases[table] else: return None def visit_extract(self, extract, **kw): field = self.extract_map.get(extract.field, extract.field) return "DATEPART(%s, %s)" % (field, self.process(extract.expr, **kw)) def visit_savepoint(self, savepoint_stmt, **kw): return "SAVE TRANSACTION %s" % self.preparer.format_savepoint( savepoint_stmt ) def visit_rollback_to_savepoint(self, savepoint_stmt, **kw): return "ROLLBACK TRANSACTION %s" % self.preparer.format_savepoint( savepoint_stmt ) def visit_binary(self, binary, **kwargs): """Move bind parameters to the right-hand side of an operator, where possible. """ if ( isinstance(binary.left, expression.BindParameter) and binary.operator == operator.eq and not isinstance(binary.right, expression.BindParameter) ): return self.process( expression.BinaryExpression( binary.right, binary.left, binary.operator ), **kwargs, ) return super().visit_binary(binary, **kwargs) def returning_clause( self, stmt, returning_cols, *, populate_result_map, **kw ): # SQL server returning clause requires that the columns refer to # the virtual table names "inserted" or "deleted". Here, we make # a simple alias of our table with that name, and then adapt the # columns we have from the list of RETURNING columns to that new name # so that they render as "inserted." / "deleted.". if stmt.is_insert or stmt.is_update: target = stmt.table.alias("inserted") elif stmt.is_delete: target = stmt.table.alias("deleted") else: assert False, "expected Insert, Update or Delete statement" adapter = sql_util.ClauseAdapter(target) # adapter.traverse() takes a column from our target table and returns # the one that is linked to the "inserted" / "deleted" tables. So in # order to retrieve these values back from the result (e.g. like # row[column]), tell the compiler to also add the original unadapted # column to the result map. Before #4877, these were (unknowingly) # falling back using string name matching in the result set which # necessarily used an expensive KeyError in order to match. columns = [ self._label_returning_column( stmt, adapter.traverse(column), populate_result_map, {"result_map_targets": (column,)}, fallback_label_name=fallback_label_name, column_is_repeated=repeated, name=name, proxy_name=proxy_name, **kw, ) for ( name, proxy_name, fallback_label_name, column, repeated, ) in stmt._generate_columns_plus_names( True, cols=expression._select_iterables(returning_cols) ) ] return "OUTPUT " + ", ".join(columns) def get_cte_preamble(self, recursive): # SQL Server finds it too inconvenient to accept # an entirely optional, SQL standard specified, # "RECURSIVE" word with their "WITH", # so here we go return "WITH" def label_select_column(self, select, column, asfrom): if isinstance(column, expression.Function): return column.label(None) else: return super().label_select_column(select, column, asfrom) def for_update_clause(self, select, **kw): # "FOR UPDATE" is only allowed on "DECLARE CURSOR" which # SQLAlchemy doesn't use return "" def order_by_clause(self, select, **kw): # MSSQL only allows ORDER BY in subqueries if there is a LIMIT: # "The ORDER BY clause is invalid in views, inline functions, # derived tables, subqueries, and common table expressions, # unless TOP, OFFSET or FOR XML is also specified." if ( self.is_subquery() and not self._use_top(select) and ( select._offset is None or not self.dialect._supports_offset_fetch ) ): # avoid processing the order by clause if we won't end up # using it, because we don't want all the bind params tacked # onto the positional list if that is what the dbapi requires return "" order_by = self.process(select._order_by_clause, **kw) if order_by: return " ORDER BY " + order_by else: return "" def update_from_clause( self, update_stmt, from_table, extra_froms, from_hints, **kw ): """Render the UPDATE..FROM clause specific to MSSQL. In MSSQL, if the UPDATE statement involves an alias of the table to be updated, then the table itself must be added to the FROM list as well. Otherwise, it is optional. Here, we add it regardless. """ return "FROM " + ", ".join( t._compiler_dispatch(self, asfrom=True, fromhints=from_hints, **kw) for t in [from_table] + extra_froms ) def delete_table_clause(self, delete_stmt, from_table, extra_froms, **kw): """If we have extra froms make sure we render any alias as hint.""" ashint = False if extra_froms: ashint = True return from_table._compiler_dispatch( self, asfrom=True, iscrud=True, ashint=ashint, **kw ) def delete_extra_from_clause( self, delete_stmt, from_table, extra_froms, from_hints, **kw ): """Render the DELETE .. FROM clause specific to MSSQL. Yes, it has the FROM keyword twice. """ return "FROM " + ", ".join( t._compiler_dispatch(self, asfrom=True, fromhints=from_hints, **kw) for t in [from_table] + extra_froms ) def visit_empty_set_expr(self, type_, **kw): return "SELECT 1 WHERE 1!=1" def visit_is_distinct_from_binary(self, binary, operator, **kw): return "NOT EXISTS (SELECT %s INTERSECT SELECT %s)" % ( self.process(binary.left), self.process(binary.right), ) def visit_is_not_distinct_from_binary(self, binary, operator, **kw): return "EXISTS (SELECT %s INTERSECT SELECT %s)" % ( self.process(binary.left), self.process(binary.right), ) def _render_json_extract_from_binary(self, binary, operator, **kw): # note we are intentionally calling upon the process() calls in the # order in which they appear in the SQL String as this is used # by positional parameter rendering if binary.type._type_affinity is sqltypes.JSON: return "JSON_QUERY(%s, %s)" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) # as with other dialects, start with an explicit test for NULL case_expression = "CASE JSON_VALUE(%s, %s) WHEN NULL THEN NULL" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) if binary.type._type_affinity is sqltypes.Integer: type_expression = "ELSE CAST(JSON_VALUE(%s, %s) AS INTEGER)" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) elif binary.type._type_affinity is sqltypes.Numeric: type_expression = "ELSE CAST(JSON_VALUE(%s, %s) AS %s)" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ( "FLOAT" if isinstance(binary.type, sqltypes.Float) else "NUMERIC(%s, %s)" % (binary.type.precision, binary.type.scale) ), ) elif binary.type._type_affinity is sqltypes.Boolean: # the NULL handling is particularly weird with boolean, so # explicitly return numeric (BIT) constants type_expression = ( "WHEN 'true' THEN 1 WHEN 'false' THEN 0 ELSE NULL" ) elif binary.type._type_affinity is sqltypes.String: # TODO: does this comment (from mysql) apply to here, too? # this fails with a JSON value that's a four byte unicode # string. SQLite has the same problem at the moment type_expression = "ELSE JSON_VALUE(%s, %s)" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) else: # other affinity....this is not expected right now type_expression = "ELSE JSON_QUERY(%s, %s)" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) return case_expression + " " + type_expression + " END" def visit_json_getitem_op_binary(self, binary, operator, **kw): return self._render_json_extract_from_binary(binary, operator, **kw) def visit_json_path_getitem_op_binary(self, binary, operator, **kw): return self._render_json_extract_from_binary(binary, operator, **kw) def visit_sequence(self, seq, **kw): return "NEXT VALUE FOR %s" % self.preparer.format_sequence(seq) class MSSQLStrictCompiler(MSSQLCompiler): """A subclass of MSSQLCompiler which disables the usage of bind parameters where not allowed natively by MS-SQL. A dialect may use this compiler on a platform where native binds are used. """ ansi_bind_rules = True def visit_in_op_binary(self, binary, operator, **kw): kw["literal_execute"] = True return "%s IN %s" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) def visit_not_in_op_binary(self, binary, operator, **kw): kw["literal_execute"] = True return "%s NOT IN %s" % ( self.process(binary.left, **kw), self.process(binary.right, **kw), ) def render_literal_value(self, value, type_): """ For date and datetime values, convert to a string format acceptable to MSSQL. That seems to be the so-called ODBC canonical date format which looks like this: yyyy-mm-dd hh:mi:ss.mmm(24h) For other data types, call the base class implementation. """ # datetime and date are both subclasses of datetime.date if issubclass(type(value), datetime.date): # SQL Server wants single quotes around the date string. return "'" + str(value) + "'" else: return super().render_literal_value(value, type_) class MSDDLCompiler(compiler.DDLCompiler): def get_column_specification(self, column, **kwargs): colspec = self.preparer.format_column(column) # type is not accepted in a computed column if column.computed is not None: colspec += " " + self.process(column.computed) else: colspec += " " + self.dialect.type_compiler_instance.process( column.type, type_expression=column ) if column.nullable is not None: if ( not column.nullable or column.primary_key or isinstance(column.default, sa_schema.Sequence) or column.autoincrement is True or column.identity ): colspec += " NOT NULL" elif column.computed is None: # don't specify "NULL" for computed columns colspec += " NULL" if column.table is None: raise exc.CompileError( "mssql requires Table-bound columns " "in order to generate DDL" ) d_opt = column.dialect_options["mssql"] start = d_opt["identity_start"] increment = d_opt["identity_increment"] if start is not None or increment is not None: if column.identity: raise exc.CompileError( "Cannot specify options 'mssql_identity_start' and/or " "'mssql_identity_increment' while also using the " "'Identity' construct." ) util.warn_deprecated( "The dialect options 'mssql_identity_start' and " "'mssql_identity_increment' are deprecated. " "Use the 'Identity' object instead.", "1.4", ) if column.identity: colspec += self.process(column.identity, **kwargs) elif ( column is column.table._autoincrement_column or column.autoincrement is True ) and ( not isinstance(column.default, Sequence) or column.default.optional ): colspec += self.process(Identity(start=start, increment=increment)) else: default = self.get_column_default_string(column) if default is not None: colspec += " DEFAULT " + default return colspec def visit_create_index(self, create, include_schema=False, **kw): index = create.element self._verify_index_table(index) preparer = self.preparer text = "CREATE " if index.unique: text += "UNIQUE " # handle clustering option clustered = index.dialect_options["mssql"]["clustered"] if clustered is not None: if clustered: text += "CLUSTERED " else: text += "NONCLUSTERED " # handle columnstore option (has no negative value) columnstore = index.dialect_options["mssql"]["columnstore"] if columnstore: text += "COLUMNSTORE " text += "INDEX %s ON %s" % ( self._prepared_index_name(index, include_schema=include_schema), preparer.format_table(index.table), ) # in some case mssql allows indexes with no columns defined if len(index.expressions) > 0: text += " (%s)" % ", ".join( self.sql_compiler.process( expr, include_table=False, literal_binds=True ) for expr in index.expressions ) # handle other included columns if index.dialect_options["mssql"]["include"]: inclusions = [ index.table.c[col] if isinstance(col, str) else col for col in index.dialect_options["mssql"]["include"] ] text += " INCLUDE (%s)" % ", ".join( [preparer.quote(c.name) for c in inclusions] ) whereclause = index.dialect_options["mssql"]["where"] if whereclause is not None: whereclause = coercions.expect( roles.DDLExpressionRole, whereclause ) where_compiled = self.sql_compiler.process( whereclause, include_table=False, literal_binds=True ) text += " WHERE " + where_compiled return text def visit_drop_index(self, drop, **kw): return "\nDROP INDEX %s ON %s" % ( self._prepared_index_name(drop.element, include_schema=False), self.preparer.format_table(drop.element.table), ) def visit_primary_key_constraint(self, constraint, **kw): if len(constraint) == 0: return "" text = "" if constraint.name is not None: text += "CONSTRAINT %s " % self.preparer.format_constraint( constraint ) text += "PRIMARY KEY " clustered = constraint.dialect_options["mssql"]["clustered"] if clustered is not None: if clustered: text += "CLUSTERED " else: text += "NONCLUSTERED " text += "(%s)" % ", ".join( self.preparer.quote(c.name) for c in constraint ) text += self.define_constraint_deferrability(constraint) return text def visit_unique_constraint(self, constraint, **kw): if len(constraint) == 0: return "" text = "" if constraint.name is not None: formatted_name = self.preparer.format_constraint(constraint) if formatted_name is not None: text += "CONSTRAINT %s " % formatted_name text += "UNIQUE %s" % self.define_unique_constraint_distinct( constraint, **kw ) clustered = constraint.dialect_options["mssql"]["clustered"] if clustered is not None: if clustered: text += "CLUSTERED " else: text += "NONCLUSTERED " text += "(%s)" % ", ".join( self.preparer.quote(c.name) for c in constraint ) text += self.define_constraint_deferrability(constraint) return text def visit_computed_column(self, generated, **kw): text = "AS (%s)" % self.sql_compiler.process( generated.sqltext, include_table=False, literal_binds=True ) # explicitly check for True|False since None means server default if generated.persisted is True: text += " PERSISTED" return text def visit_set_table_comment(self, create, **kw): schema = self.preparer.schema_for_object(create.element) schema_name = schema if schema else self.dialect.default_schema_name return ( "execute sp_addextendedproperty 'MS_Description', " "{}, 'schema', {}, 'table', {}".format( self.sql_compiler.render_literal_value( create.element.comment, sqltypes.NVARCHAR() ), self.preparer.quote_schema(schema_name), self.preparer.format_table(create.element, use_schema=False), ) ) def visit_drop_table_comment(self, drop, **kw): schema = self.preparer.schema_for_object(drop.element) schema_name = schema if schema else self.dialect.default_schema_name return ( "execute sp_dropextendedproperty 'MS_Description', 'schema', " "{}, 'table', {}".format( self.preparer.quote_schema(schema_name), self.preparer.format_table(drop.element, use_schema=False), ) ) def visit_set_column_comment(self, create, **kw): schema = self.preparer.schema_for_object(create.element.table) schema_name = schema if schema else self.dialect.default_schema_name return ( "execute sp_addextendedproperty 'MS_Description', " "{}, 'schema', {}, 'table', {}, 'column', {}".format( self.sql_compiler.render_literal_value( create.element.comment, sqltypes.NVARCHAR() ), self.preparer.quote_schema(schema_name), self.preparer.format_table( create.element.table, use_schema=False ), self.preparer.format_column(create.element), ) ) def visit_drop_column_comment(self, drop, **kw): schema = self.preparer.schema_for_object(drop.element.table) schema_name = schema if schema else self.dialect.default_schema_name return ( "execute sp_dropextendedproperty 'MS_Description', 'schema', " "{}, 'table', {}, 'column', {}".format( self.preparer.quote_schema(schema_name), self.preparer.format_table( drop.element.table, use_schema=False ), self.preparer.format_column(drop.element), ) ) def visit_create_sequence(self, create, **kw): prefix = None if create.element.data_type is not None: data_type = create.element.data_type prefix = " AS %s" % self.type_compiler.process(data_type) return super().visit_create_sequence(create, prefix=prefix, **kw) def visit_identity_column(self, identity, **kw): text = " IDENTITY" if identity.start is not None or identity.increment is not None: start = 1 if identity.start is None else identity.start increment = 1 if identity.increment is None else identity.increment text += "(%s,%s)" % (start, increment) return text class MSIdentifierPreparer(compiler.IdentifierPreparer): reserved_words = RESERVED_WORDS def __init__(self, dialect): super().__init__( dialect, initial_quote="[", final_quote="]", quote_case_sensitive_collations=False, ) def _escape_identifier(self, value): return value.replace("]", "]]") def _unescape_identifier(self, value): return value.replace("]]", "]") def quote_schema(self, schema, force=None): """Prepare a quoted table and schema name.""" # need to re-implement the deprecation warning entirely if force is not None: # not using the util.deprecated_params() decorator in this # case because of the additional function call overhead on this # very performance-critical spot. util.warn_deprecated( "The IdentifierPreparer.quote_schema.force parameter is " "deprecated and will be removed in a future release. This " "flag has no effect on the behavior of the " "IdentifierPreparer.quote method; please refer to " "quoted_name().", version="1.3", ) dbname, owner = _schema_elements(schema) if dbname: result = "%s.%s" % (self.quote(dbname), self.quote(owner)) elif owner: result = self.quote(owner) else: result = "" return result def _db_plus_owner_listing(fn): def wrap(dialect, connection, schema=None, **kw): dbname, owner = _owner_plus_db(dialect, schema) return _switch_db( dbname, connection, fn, dialect, connection, dbname, owner, schema, **kw, ) return update_wrapper(wrap, fn) def _db_plus_owner(fn): def wrap(dialect, connection, tablename, schema=None, **kw): dbname, owner = _owner_plus_db(dialect, schema) return _switch_db( dbname, connection, fn, dialect, connection, tablename, dbname, owner, schema, **kw, ) return update_wrapper(wrap, fn) def _switch_db(dbname, connection, fn, *arg, **kw): if dbname: current_db = connection.exec_driver_sql("select db_name()").scalar() if current_db != dbname: connection.exec_driver_sql( "use %s" % connection.dialect.identifier_preparer.quote(dbname) ) try: return fn(*arg, **kw) finally: if dbname and current_db != dbname: connection.exec_driver_sql( "use %s" % connection.dialect.identifier_preparer.quote(current_db) ) def _owner_plus_db(dialect, schema): if not schema: return None, dialect.default_schema_name else: return _schema_elements(schema) _memoized_schema = util.LRUCache() def _schema_elements(schema): if isinstance(schema, quoted_name) and schema.quote: return None, schema if schema in _memoized_schema: return _memoized_schema[schema] # tests for this function are in: # test/dialect/mssql/test_reflection.py -> # OwnerPlusDBTest.test_owner_database_pairs # test/dialect/mssql/test_compiler.py -> test_force_schema_* # test/dialect/mssql/test_compiler.py -> test_schema_many_tokens_* # if schema.startswith("__[SCHEMA_"): return None, schema push = [] symbol = "" bracket = False has_brackets = False for token in re.split(r"(\[|\]|\.)", schema): if not token: continue if token == "[": bracket = True has_brackets = True elif token == "]": bracket = False elif not bracket and token == ".": if has_brackets: push.append("[%s]" % symbol) else: push.append(symbol) symbol = "" has_brackets = False else: symbol += token if symbol: push.append(symbol) if len(push) > 1: dbname, owner = ".".join(push[0:-1]), push[-1] # test for internal brackets if re.match(r".*\].*\[.*", dbname[1:-1]): dbname = quoted_name(dbname, quote=False) else: dbname = dbname.lstrip("[").rstrip("]") elif len(push): dbname, owner = None, push[0] else: dbname, owner = None, None _memoized_schema[schema] = dbname, owner return dbname, owner class MSDialect(default.DefaultDialect): # will assume it's at least mssql2005 name = "mssql" supports_statement_cache = True supports_default_values = True supports_empty_insert = False favor_returning_over_lastrowid = True returns_native_bytes = True supports_comments = True supports_default_metavalue = False """dialect supports INSERT... VALUES (DEFAULT) syntax - SQL Server **does** support this, but **not** for the IDENTITY column, so we can't turn this on. """ # supports_native_uuid is partial here, so we implement our # own impl type execution_ctx_cls = MSExecutionContext use_scope_identity = True max_identifier_length = 128 schema_name = "dbo" insert_returning = True update_returning = True delete_returning = True update_returning_multifrom = True delete_returning_multifrom = True colspecs = { sqltypes.DateTime: _MSDateTime, sqltypes.Date: _MSDate, sqltypes.JSON: JSON, sqltypes.JSON.JSONIndexType: JSONIndexType, sqltypes.JSON.JSONPathType: JSONPathType, sqltypes.Time: _BASETIMEIMPL, sqltypes.Unicode: _MSUnicode, sqltypes.UnicodeText: _MSUnicodeText, DATETIMEOFFSET: DATETIMEOFFSET, DATETIME2: DATETIME2, SMALLDATETIME: SMALLDATETIME, DATETIME: DATETIME, sqltypes.Uuid: MSUUid, } engine_config_types = default.DefaultDialect.engine_config_types.union( {"legacy_schema_aliasing": util.asbool} ) ischema_names = ischema_names supports_sequences = True sequences_optional = True # This is actually used for autoincrement, where itentity is used that # starts with 1. # for sequences T-SQL's actual default is -9223372036854775808 default_sequence_base = 1 supports_native_boolean = False non_native_boolean_check_constraint = False supports_unicode_binds = True postfetch_lastrowid = True # may be changed at server inspection time for older SQL server versions supports_multivalues_insert = True use_insertmanyvalues = True # note pyodbc will set this to False if fast_executemany is set, # as of SQLAlchemy 2.0.9 use_insertmanyvalues_wo_returning = True insertmanyvalues_implicit_sentinel = ( InsertmanyvaluesSentinelOpts.AUTOINCREMENT | InsertmanyvaluesSentinelOpts.IDENTITY | InsertmanyvaluesSentinelOpts.USE_INSERT_FROM_SELECT ) # "The incoming request has too many parameters. The server supports a " # "maximum of 2100 parameters." # in fact you can have 2099 parameters. insertmanyvalues_max_parameters = 2099 _supports_offset_fetch = False _supports_nvarchar_max = False legacy_schema_aliasing = False server_version_info = () statement_compiler = MSSQLCompiler ddl_compiler = MSDDLCompiler type_compiler_cls = MSTypeCompiler preparer = MSIdentifierPreparer construct_arguments = [ (sa_schema.PrimaryKeyConstraint, {"clustered": None}), (sa_schema.UniqueConstraint, {"clustered": None}), ( sa_schema.Index, { "clustered": None, "include": None, "where": None, "columnstore": None, }, ), ( sa_schema.Column, {"identity_start": None, "identity_increment": None}, ), ] def __init__( self, query_timeout=None, use_scope_identity=True, schema_name="dbo", deprecate_large_types=None, supports_comments=None, json_serializer=None, json_deserializer=None, legacy_schema_aliasing=None, ignore_no_transaction_on_rollback=False, **opts, ): self.query_timeout = int(query_timeout or 0) self.schema_name = schema_name self.use_scope_identity = use_scope_identity self.deprecate_large_types = deprecate_large_types self.ignore_no_transaction_on_rollback = ( ignore_no_transaction_on_rollback ) self._user_defined_supports_comments = uds = supports_comments if uds is not None: self.supports_comments = uds if legacy_schema_aliasing is not None: util.warn_deprecated( "The legacy_schema_aliasing parameter is " "deprecated and will be removed in a future release.", "1.4", ) self.legacy_schema_aliasing = legacy_schema_aliasing super().__init__(**opts) self._json_serializer = json_serializer self._json_deserializer = json_deserializer def do_savepoint(self, connection, name): # give the DBAPI a push connection.exec_driver_sql("IF @@TRANCOUNT = 0 BEGIN TRANSACTION") super().do_savepoint(connection, name) def do_release_savepoint(self, connection, name): # SQL Server does not support RELEASE SAVEPOINT pass def do_rollback(self, dbapi_connection): try: super().do_rollback(dbapi_connection) except self.dbapi.ProgrammingError as e: if self.ignore_no_transaction_on_rollback and re.match( r".*\b111214\b", str(e) ): util.warn( "ProgrammingError 111214 " "'No corresponding transaction found.' " "has been suppressed via " "ignore_no_transaction_on_rollback=True" ) else: raise _isolation_lookup = { "SERIALIZABLE", "READ UNCOMMITTED", "READ COMMITTED", "REPEATABLE READ", "SNAPSHOT", } def get_isolation_level_values(self, dbapi_connection): return list(self._isolation_lookup) def set_isolation_level(self, dbapi_connection, level): cursor = dbapi_connection.cursor() cursor.execute(f"SET TRANSACTION ISOLATION LEVEL {level}") cursor.close() if level == "SNAPSHOT": dbapi_connection.commit() def get_isolation_level(self, dbapi_connection): cursor = dbapi_connection.cursor() view_name = "sys.system_views" try: cursor.execute( ( "SELECT name FROM {} WHERE name IN " "('dm_exec_sessions', 'dm_pdw_nodes_exec_sessions')" ).format(view_name) ) row = cursor.fetchone() if not row: raise NotImplementedError( "Can't fetch isolation level on this particular " "SQL Server version." ) view_name = f"sys.{row[0]}" cursor.execute( """ SELECT CASE transaction_isolation_level WHEN 0 THEN NULL WHEN 1 THEN 'READ UNCOMMITTED' WHEN 2 THEN 'READ COMMITTED' WHEN 3 THEN 'REPEATABLE READ' WHEN 4 THEN 'SERIALIZABLE' WHEN 5 THEN 'SNAPSHOT' END AS TRANSACTION_ISOLATION_LEVEL FROM {} where session_id = @@SPID """.format( view_name ) ) except self.dbapi.Error as err: raise NotImplementedError( "Can't fetch isolation level; encountered error {} when " 'attempting to query the "{}" view.'.format(err, view_name) ) from err else: row = cursor.fetchone() return row[0].upper() finally: cursor.close() def initialize(self, connection): super().initialize(connection) self._setup_version_attributes() self._setup_supports_nvarchar_max(connection) self._setup_supports_comments(connection) def _setup_version_attributes(self): if self.server_version_info[0] not in list(range(8, 17)): util.warn( "Unrecognized server version info '%s'. Some SQL Server " "features may not function properly." % ".".join(str(x) for x in self.server_version_info) ) if self.server_version_info >= MS_2008_VERSION: self.supports_multivalues_insert = True else: self.supports_multivalues_insert = False if self.deprecate_large_types is None: self.deprecate_large_types = ( self.server_version_info >= MS_2012_VERSION ) self._supports_offset_fetch = ( self.server_version_info and self.server_version_info[0] >= 11 ) def _setup_supports_nvarchar_max(self, connection): try: connection.scalar( sql.text("SELECT CAST('test max support' AS NVARCHAR(max))") ) except exc.DBAPIError: self._supports_nvarchar_max = False else: self._supports_nvarchar_max = True def _setup_supports_comments(self, connection): if self._user_defined_supports_comments is not None: return try: connection.scalar( sql.text( "SELECT 1 FROM fn_listextendedproperty" "(default, default, default, default, " "default, default, default)" ) ) except exc.DBAPIError: self.supports_comments = False else: self.supports_comments = True def _get_default_schema_name(self, connection): query = sql.text("SELECT schema_name()") default_schema_name = connection.scalar(query) if default_schema_name is not None: # guard against the case where the default_schema_name is being # fed back into a table reflection function. return quoted_name(default_schema_name, quote=True) else: return self.schema_name @_db_plus_owner def has_table(self, connection, tablename, dbname, owner, schema, **kw): self._ensure_has_table_connection(connection) return self._internal_has_table(connection, tablename, owner, **kw) @reflection.cache @_db_plus_owner def has_sequence( self, connection, sequencename, dbname, owner, schema, **kw ): sequences = ischema.sequences s = sql.select(sequences.c.sequence_name).where( sequences.c.sequence_name == sequencename ) if owner: s = s.where(sequences.c.sequence_schema == owner) c = connection.execute(s) return c.first() is not None @reflection.cache @_db_plus_owner_listing def get_sequence_names(self, connection, dbname, owner, schema, **kw): sequences = ischema.sequences s = sql.select(sequences.c.sequence_name) if owner: s = s.where(sequences.c.sequence_schema == owner) c = connection.execute(s) return [row[0] for row in c] @reflection.cache def get_schema_names(self, connection, **kw): s = sql.select(ischema.schemata.c.schema_name).order_by( ischema.schemata.c.schema_name ) schema_names = [r[0] for r in connection.execute(s)] return schema_names @reflection.cache @_db_plus_owner_listing def get_table_names(self, connection, dbname, owner, schema, **kw): tables = ischema.tables s = ( sql.select(tables.c.table_name) .where( sql.and_( tables.c.table_schema == owner, tables.c.table_type == "BASE TABLE", ) ) .order_by(tables.c.table_name) ) table_names = [r[0] for r in connection.execute(s)] return table_names @reflection.cache @_db_plus_owner_listing def get_view_names(self, connection, dbname, owner, schema, **kw): tables = ischema.tables s = ( sql.select(tables.c.table_name) .where( sql.and_( tables.c.table_schema == owner, tables.c.table_type == "VIEW", ) ) .order_by(tables.c.table_name) ) view_names = [r[0] for r in connection.execute(s)] return view_names @reflection.cache def _internal_has_table(self, connection, tablename, owner, **kw): if tablename.startswith("#"): # temporary table # mssql does not support temporary views # SQL Error [4103] [S0001]: "#v": Temporary views are not allowed return bool( connection.scalar( # U filters on user tables only. text("SELECT object_id(:table_name, 'U')"), {"table_name": f"tempdb.dbo.[{tablename}]"}, ) ) else: tables = ischema.tables s = sql.select(tables.c.table_name).where( sql.and_( sql.or_( tables.c.table_type == "BASE TABLE", tables.c.table_type == "VIEW", ), tables.c.table_name == tablename, ) ) if owner: s = s.where(tables.c.table_schema == owner) c = connection.execute(s) return c.first() is not None def _default_or_error(self, connection, tablename, owner, method, **kw): # TODO: try to avoid having to run a separate query here if self._internal_has_table(connection, tablename, owner, **kw): return method() else: raise exc.NoSuchTableError(f"{owner}.{tablename}") @reflection.cache @_db_plus_owner def get_indexes(self, connection, tablename, dbname, owner, schema, **kw): filter_definition = ( "ind.filter_definition" if self.server_version_info >= MS_2008_VERSION else "NULL as filter_definition" ) rp = connection.execution_options(future_result=True).execute( sql.text( f""" select ind.index_id, ind.is_unique, ind.name, ind.type, {filter_definition} from sys.indexes as ind join sys.tables as tab on ind.object_id = tab.object_id join sys.schemas as sch on sch.schema_id = tab.schema_id where tab.name = :tabname and sch.name = :schname and ind.is_primary_key = 0 and ind.type != 0 order by ind.name """ ) .bindparams( sql.bindparam("tabname", tablename, ischema.CoerceUnicode()), sql.bindparam("schname", owner, ischema.CoerceUnicode()), ) .columns(name=sqltypes.Unicode()) ) indexes = {} for row in rp.mappings(): indexes[row["index_id"]] = current = { "name": row["name"], "unique": row["is_unique"] == 1, "column_names": [], "include_columns": [], "dialect_options": {}, } do = current["dialect_options"] index_type = row["type"] if index_type in {1, 2}: do["mssql_clustered"] = index_type == 1 if index_type in {5, 6}: do["mssql_clustered"] = index_type == 5 do["mssql_columnstore"] = True if row["filter_definition"] is not None: do["mssql_where"] = row["filter_definition"] rp = connection.execution_options(future_result=True).execute( sql.text( """ select ind_col.index_id, col.name, ind_col.is_included_column from sys.columns as col join sys.tables as tab on tab.object_id = col.object_id join sys.index_columns as ind_col on ind_col.column_id = col.column_id and ind_col.object_id = tab.object_id join sys.schemas as sch on sch.schema_id = tab.schema_id where tab.name = :tabname and sch.name = :schname """ ) .bindparams( sql.bindparam("tabname", tablename, ischema.CoerceUnicode()), sql.bindparam("schname", owner, ischema.CoerceUnicode()), ) .columns(name=sqltypes.Unicode()) ) for row in rp.mappings(): if row["index_id"] not in indexes: continue index_def = indexes[row["index_id"]] is_colstore = index_def["dialect_options"].get("mssql_columnstore") is_clustered = index_def["dialect_options"].get("mssql_clustered") if not (is_colstore and is_clustered): # a clustered columnstore index includes all columns but does # not want them in the index definition if row["is_included_column"] and not is_colstore: # a noncludsted columnstore index reports that includes # columns but requires that are listed as normal columns index_def["include_columns"].append(row["name"]) else: index_def["column_names"].append(row["name"]) for index_info in indexes.values(): # NOTE: "root level" include_columns is legacy, now part of # dialect_options (issue #7382) index_info["dialect_options"]["mssql_include"] = index_info[ "include_columns" ] if indexes: return list(indexes.values()) else: return self._default_or_error( connection, tablename, owner, ReflectionDefaults.indexes, **kw ) @reflection.cache @_db_plus_owner def get_view_definition( self, connection, viewname, dbname, owner, schema, **kw ): view_def = connection.execute( sql.text( "select mod.definition " "from sys.sql_modules as mod " "join sys.views as views on mod.object_id = views.object_id " "join sys.schemas as sch on views.schema_id = sch.schema_id " "where views.name=:viewname and sch.name=:schname" ).bindparams( sql.bindparam("viewname", viewname, ischema.CoerceUnicode()), sql.bindparam("schname", owner, ischema.CoerceUnicode()), ) ).scalar() if view_def: return view_def else: raise exc.NoSuchTableError(f"{owner}.{viewname}") @reflection.cache def get_table_comment(self, connection, table_name, schema=None, **kw): if not self.supports_comments: raise NotImplementedError( "Can't get table comments on current SQL Server version in use" ) schema_name = schema if schema else self.default_schema_name COMMENT_SQL = """ SELECT cast(com.value as nvarchar(max)) FROM fn_listextendedproperty('MS_Description', 'schema', :schema, 'table', :table, NULL, NULL ) as com; """ comment = connection.execute( sql.text(COMMENT_SQL).bindparams( sql.bindparam("schema", schema_name, ischema.CoerceUnicode()), sql.bindparam("table", table_name, ischema.CoerceUnicode()), ) ).scalar() if comment: return {"text": comment} else: return self._default_or_error( connection, table_name, None, ReflectionDefaults.table_comment, **kw, ) def _temp_table_name_like_pattern(self, tablename): # LIKE uses '%' to match zero or more characters and '_' to match any # single character. We want to match literal underscores, so T-SQL # requires that we enclose them in square brackets. return tablename + ( ("[_][_][_]%") if not tablename.startswith("##") else "" ) def _get_internal_temp_table_name(self, connection, tablename): # it's likely that schema is always "dbo", but since we can # get it here, let's get it. # see https://stackoverflow.com/questions/8311959/ # specifying-schema-for-temporary-tables try: return connection.execute( sql.text( "select table_schema, table_name " "from tempdb.information_schema.tables " "where table_name like :p1" ), {"p1": self._temp_table_name_like_pattern(tablename)}, ).one() except exc.MultipleResultsFound as me: raise exc.UnreflectableTableError( "Found more than one temporary table named '%s' in tempdb " "at this time. Cannot reliably resolve that name to its " "internal table name." % tablename ) from me except exc.NoResultFound as ne: raise exc.NoSuchTableError( "Unable to find a temporary table named '%s' in tempdb." % tablename ) from ne @reflection.cache @_db_plus_owner def get_columns(self, connection, tablename, dbname, owner, schema, **kw): is_temp_table = tablename.startswith("#") if is_temp_table: owner, tablename = self._get_internal_temp_table_name( connection, tablename ) columns = ischema.mssql_temp_table_columns else: columns = ischema.columns computed_cols = ischema.computed_columns identity_cols = ischema.identity_columns if owner: whereclause = sql.and_( columns.c.table_name == tablename, columns.c.table_schema == owner, ) full_name = columns.c.table_schema + "." + columns.c.table_name else: whereclause = columns.c.table_name == tablename full_name = columns.c.table_name if self._supports_nvarchar_max: computed_definition = computed_cols.c.definition else: # tds_version 4.2 does not support NVARCHAR(MAX) computed_definition = sql.cast( computed_cols.c.definition, NVARCHAR(4000) ) object_id = func.object_id(full_name) s = ( sql.select( columns.c.column_name, columns.c.data_type, columns.c.is_nullable, columns.c.character_maximum_length, columns.c.numeric_precision, columns.c.numeric_scale, columns.c.column_default, columns.c.collation_name, computed_definition, computed_cols.c.is_persisted, identity_cols.c.is_identity, identity_cols.c.seed_value, identity_cols.c.increment_value, ischema.extended_properties.c.value.label("comment"), ) .select_from(columns) .outerjoin( computed_cols, onclause=sql.and_( computed_cols.c.object_id == object_id, computed_cols.c.name == columns.c.column_name.collate("DATABASE_DEFAULT"), ), ) .outerjoin( identity_cols, onclause=sql.and_( identity_cols.c.object_id == object_id, identity_cols.c.name == columns.c.column_name.collate("DATABASE_DEFAULT"), ), ) .outerjoin( ischema.extended_properties, onclause=sql.and_( ischema.extended_properties.c["class"] == 1, ischema.extended_properties.c.major_id == object_id, ischema.extended_properties.c.minor_id == columns.c.ordinal_position, ischema.extended_properties.c.name == "MS_Description", ), ) .where(whereclause) .order_by(columns.c.ordinal_position) ) c = connection.execution_options(future_result=True).execute(s) cols = [] for row in c.mappings(): name = row[columns.c.column_name] type_ = row[columns.c.data_type] nullable = row[columns.c.is_nullable] == "YES" charlen = row[columns.c.character_maximum_length] numericprec = row[columns.c.numeric_precision] numericscale = row[columns.c.numeric_scale] default = row[columns.c.column_default] collation = row[columns.c.collation_name] definition = row[computed_definition] is_persisted = row[computed_cols.c.is_persisted] is_identity = row[identity_cols.c.is_identity] identity_start = row[identity_cols.c.seed_value] identity_increment = row[identity_cols.c.increment_value] comment = row[ischema.extended_properties.c.value] coltype = self.ischema_names.get(type_, None) kwargs = {} if coltype in ( MSString, MSChar, MSNVarchar, MSNChar, MSText, MSNText, MSBinary, MSVarBinary, sqltypes.LargeBinary, ): if charlen == -1: charlen = None kwargs["length"] = charlen if collation: kwargs["collation"] = collation if coltype is None: util.warn( "Did not recognize type '%s' of column '%s'" % (type_, name) ) coltype = sqltypes.NULLTYPE else: if issubclass(coltype, sqltypes.Numeric): kwargs["precision"] = numericprec if not issubclass(coltype, sqltypes.Float): kwargs["scale"] = numericscale coltype = coltype(**kwargs) cdict = { "name": name, "type": coltype, "nullable": nullable, "default": default, "autoincrement": is_identity is not None, "comment": comment, } if definition is not None and is_persisted is not None: cdict["computed"] = { "sqltext": definition, "persisted": is_persisted, } if is_identity is not None: # identity_start and identity_increment are Decimal or None if identity_start is None or identity_increment is None: cdict["identity"] = {} else: if isinstance(coltype, sqltypes.BigInteger): start = int(identity_start) increment = int(identity_increment) elif isinstance(coltype, sqltypes.Integer): start = int(identity_start) increment = int(identity_increment) else: start = identity_start increment = identity_increment cdict["identity"] = { "start": start, "increment": increment, } cols.append(cdict) if cols: return cols else: return self._default_or_error( connection, tablename, owner, ReflectionDefaults.columns, **kw ) @reflection.cache @_db_plus_owner def get_pk_constraint( self, connection, tablename, dbname, owner, schema, **kw ): pkeys = [] TC = ischema.constraints C = ischema.key_constraints.alias("C") # Primary key constraints s = ( sql.select( C.c.column_name, TC.c.constraint_type, C.c.constraint_name, func.objectproperty( func.object_id( C.c.table_schema + "." + C.c.constraint_name ), "CnstIsClustKey", ).label("is_clustered"), ) .where( sql.and_( TC.c.constraint_name == C.c.constraint_name, TC.c.table_schema == C.c.table_schema, C.c.table_name == tablename, C.c.table_schema == owner, ), ) .order_by(TC.c.constraint_name, C.c.ordinal_position) ) c = connection.execution_options(future_result=True).execute(s) constraint_name = None is_clustered = None for row in c.mappings(): if "PRIMARY" in row[TC.c.constraint_type.name]: pkeys.append(row["COLUMN_NAME"]) if constraint_name is None: constraint_name = row[C.c.constraint_name.name] if is_clustered is None: is_clustered = row["is_clustered"] if pkeys: return { "constrained_columns": pkeys, "name": constraint_name, "dialect_options": {"mssql_clustered": is_clustered}, } else: return self._default_or_error( connection, tablename, owner, ReflectionDefaults.pk_constraint, **kw, ) @reflection.cache @_db_plus_owner def get_foreign_keys( self, connection, tablename, dbname, owner, schema, **kw ): # Foreign key constraints s = ( text( """\ WITH fk_info AS ( SELECT ischema_ref_con.constraint_schema, ischema_ref_con.constraint_name, ischema_key_col.ordinal_position, ischema_key_col.table_schema, ischema_key_col.table_name, ischema_ref_con.unique_constraint_schema, ischema_ref_con.unique_constraint_name, ischema_ref_con.match_option, ischema_ref_con.update_rule, ischema_ref_con.delete_rule, ischema_key_col.column_name AS constrained_column FROM INFORMATION_SCHEMA.REFERENTIAL_CONSTRAINTS ischema_ref_con INNER JOIN INFORMATION_SCHEMA.KEY_COLUMN_USAGE ischema_key_col ON ischema_key_col.table_schema = ischema_ref_con.constraint_schema AND ischema_key_col.constraint_name = ischema_ref_con.constraint_name WHERE ischema_key_col.table_name = :tablename AND ischema_key_col.table_schema = :owner ), constraint_info AS ( SELECT ischema_key_col.constraint_schema, ischema_key_col.constraint_name, ischema_key_col.ordinal_position, ischema_key_col.table_schema, ischema_key_col.table_name, ischema_key_col.column_name FROM INFORMATION_SCHEMA.KEY_COLUMN_USAGE ischema_key_col ), index_info AS ( SELECT sys.schemas.name AS index_schema, sys.indexes.name AS index_name, sys.index_columns.key_ordinal AS ordinal_position, sys.schemas.name AS table_schema, sys.objects.name AS table_name, sys.columns.name AS column_name FROM sys.indexes INNER JOIN sys.objects ON sys.objects.object_id = sys.indexes.object_id INNER JOIN sys.schemas ON sys.schemas.schema_id = sys.objects.schema_id INNER JOIN sys.index_columns ON sys.index_columns.object_id = sys.objects.object_id AND sys.index_columns.index_id = sys.indexes.index_id INNER JOIN sys.columns ON sys.columns.object_id = sys.indexes.object_id AND sys.columns.column_id = sys.index_columns.column_id ) SELECT fk_info.constraint_schema, fk_info.constraint_name, fk_info.ordinal_position, fk_info.constrained_column, constraint_info.table_schema AS referred_table_schema, constraint_info.table_name AS referred_table_name, constraint_info.column_name AS referred_column, fk_info.match_option, fk_info.update_rule, fk_info.delete_rule FROM fk_info INNER JOIN constraint_info ON constraint_info.constraint_schema = fk_info.unique_constraint_schema AND constraint_info.constraint_name = fk_info.unique_constraint_name AND constraint_info.ordinal_position = fk_info.ordinal_position UNION SELECT fk_info.constraint_schema, fk_info.constraint_name, fk_info.ordinal_position, fk_info.constrained_column, index_info.table_schema AS referred_table_schema, index_info.table_name AS referred_table_name, index_info.column_name AS referred_column, fk_info.match_option, fk_info.update_rule, fk_info.delete_rule FROM fk_info INNER JOIN index_info ON index_info.index_schema = fk_info.unique_constraint_schema AND index_info.index_name = fk_info.unique_constraint_name AND index_info.ordinal_position = fk_info.ordinal_position ORDER BY fk_info.constraint_schema, fk_info.constraint_name, fk_info.ordinal_position """ ) .bindparams( sql.bindparam("tablename", tablename, ischema.CoerceUnicode()), sql.bindparam("owner", owner, ischema.CoerceUnicode()), ) .columns( constraint_schema=sqltypes.Unicode(), constraint_name=sqltypes.Unicode(), table_schema=sqltypes.Unicode(), table_name=sqltypes.Unicode(), constrained_column=sqltypes.Unicode(), referred_table_schema=sqltypes.Unicode(), referred_table_name=sqltypes.Unicode(), referred_column=sqltypes.Unicode(), ) ) # group rows by constraint ID, to handle multi-column FKs fkeys = [] def fkey_rec(): return { "name": None, "constrained_columns": [], "referred_schema": None, "referred_table": None, "referred_columns": [], "options": {}, } fkeys = util.defaultdict(fkey_rec) for r in connection.execute(s).all(): ( _, # constraint schema rfknm, _, # ordinal position scol, rschema, rtbl, rcol, # TODO: we support match= for foreign keys so # we can support this also, PG has match=FULL for example # but this seems to not be a valid value for SQL Server _, # match rule fkuprule, fkdelrule, ) = r rec = fkeys[rfknm] rec["name"] = rfknm if fkuprule != "NO ACTION": rec["options"]["onupdate"] = fkuprule if fkdelrule != "NO ACTION": rec["options"]["ondelete"] = fkdelrule if not rec["referred_table"]: rec["referred_table"] = rtbl if schema is not None or owner != rschema: if dbname: rschema = dbname + "." + rschema rec["referred_schema"] = rschema local_cols, remote_cols = ( rec["constrained_columns"], rec["referred_columns"], ) local_cols.append(scol) remote_cols.append(rcol) if fkeys: return list(fkeys.values()) else: return self._default_or_error( connection, tablename, owner, ReflectionDefaults.foreign_keys, **kw, )