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# dialects/mssql/base.py
# Copyright (C) 2005-2026 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: https://www.opensource.org/licenses/mit-license.php
# mypy: ignore-errors
"""
.. dialect:: mssql
:name: Microsoft SQL Server
: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.
.. 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.
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:
.. sourcecode:: sql
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:
.. sourcecode:: sql
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:
.. sourcecode:: sql
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 <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 <pool_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:
.. sourcecode:: sql
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:
.. sourcecode:: sql
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 <https://technet.microsoft.com/en-us/library/ms187993.aspx>`_,
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]",
)
.. _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:
.. sourcecode:: sql
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:
.. sourcecode:: sql
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``.
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:
.. sourcecode:: sql
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
from functools import lru_cache
import operator
import re
from typing import Any
from typing import Literal
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 ObjectKind
from ...engine import ObjectScope
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 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 AggregateOrderByStyle
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
if TYPE_CHECKING:
from ...sql.ddl import DropIndex
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.
.. 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.
"""
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.
.. 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 <class 'bool'> 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):
_embedded_scope_identity = False
_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,
)
# don't embed the scope_identity select into an
# "INSERT .. DEFAULT VALUES"
if (
self._select_lastrowid
and self.dialect.scope_identity_must_be_embedded
and self.dialect.use_scope_identity
and len(self.parameters[0])
):
self._embedded_scope_identity = True
self.statement += "; select scope_identity()"
def post_exec(self):
conn = self.root_connection
if self.isinsert or self.isupdate or self.isdelete:
self._rowcount = self.cursor.rowcount
# handle INSERT with embedded SELECT SCOPE_IDENTITY() call
if self._embedded_scope_identity:
# Fetch the last inserted id from the manipulated statement
# We may have to skip over a number of result sets with
# no data (due to triggers, etc.) so run up to three times
row = None
for _ in range(3):
if self.cursor.description:
rows = self.cursor.fetchall()
if rows:
row = rows[0]
break
else:
self.cursor.nextset()
self._lastrowid = int(row[0]) if row else None
self.cursor_fetch_strategy = _cursor._NO_CURSOR_DML
elif 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:
# Disable IDENTITY_INSERT if enabled.
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 visit_frame_clause(self, frameclause, **kw):
kw["literal_execute"] = True
return super().visit_frame_clause(frameclause, **kw)
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):
cl = list(fn.clauses)
expr, delimiter = cl[0:2]
literal_exec = dict(kw)
literal_exec["literal_execute"] = True
return (
f"string_agg({expr._compiler_dispatch(self, **kw)}, "
f"{delimiter._compiler_dispatch(self, **literal_exec)})"
)
def visit_pow_func(self, fn, **kw):
return f"POWER{self.function_argspec(fn)}"
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_truediv_binary(self, binary, operator, **kw):
return (
self.process(binary.left, **kw)
+ " / "
+ f"({self.process(binary.right, **kw)} + 0.0)"
)
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.<colname>" / "deleted.<colname>".
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 in (sqltypes.Numeric, sqltypes.Float):
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 "
"CAST(JSON_VALUE(%s, %s) AS BIT)"
% (
self.process(binary.left, **kw),
self.process(binary.right, **kw),
)
)
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: DropIndex, **kw: Any) -> str:
index_name = self._prepared_index_name(
drop.element, include_schema=False
)
table_name = self.preparer.format_table(drop.element.table)
if_exists = " IF EXISTS" if drop.if_exists else ""
return f"\nDROP INDEX{if_exists} {index_name} ON {table_name}"
def visit_create_table_as(self, element, **kw):
prep = self.preparer
# SQL Server doesn't support CREATE TABLE AS, use SELECT INTO instead
# Format: SELECT columns INTO new_table FROM source WHERE ...
qualified = prep.format_table(element.table)
# Get the inner SELECT SQL
inner_kw = dict(kw)
inner_kw["literal_binds"] = True
select_sql = self.sql_compiler.process(element.selectable, **inner_kw)
# Inject INTO clause before FROM keyword
# Find FROM position (case-insensitive)
select_upper = select_sql.upper()
from_idx = select_upper.find(" FROM ")
if from_idx == -1:
from_idx = select_upper.find("\nFROM ")
if from_idx == -1:
raise exc.CompileError(
"Could not find FROM keyword in selectable for CREATE TABLE AS"
)
# Insert INTO clause before FROM
result = (
select_sql[:from_idx]
+ f"INTO {qualified} "
+ select_sql[from_idx:]
)
return result
def visit_create_view(self, create, **kw):
# SQL Server uses CREATE OR ALTER instead of CREATE OR REPLACE
result = super().visit_create_view(create, **kw)
if create.or_replace:
result = result.replace("CREATE OR REPLACE", "CREATE OR ALTER")
return result
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):
"""Prepare a quoted table and schema name."""
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 _db_plus_owner_multi(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 _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._BackendsMultiReflection, 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
scope_identity_must_be_embedded = False
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.
"""
aggregate_order_by_style = AggregateOrderByStyle.WITHIN_GROUP
# 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 min_year_for_type(self, typeobj):
typeobj = sqltypes.to_instance(typeobj)
if isinstance(typeobj, SMALLDATETIME):
return 1900
elif isinstance(typeobj, (DATETIME2, DATETIMEOFFSET)):
return datetime.MINYEAR
elif isinstance(typeobj, sqltypes.DateTime):
# DateTime renders DATETIMEOFFSET with timezone=True,
# else DATETIME
return datetime.MINYEAR if typeobj.timezone else 1753
elif (
isinstance(typeobj, sqltypes.Date)
and not isinstance(typeobj, sqltypes.DATE)
and self.server_version_info < MS_2008_VERSION
):
# Date renders DATETIME before SQL Server 2008
return 1753
else:
return datetime.MINYEAR
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 >= 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
@reflection.cache
@_db_plus_owner
def has_table(self, connection, tablename, dbname, owner, schema, **kw):
self._ensure_has_table_connection(connection)
return self._internal_has_multi_table(
connection, [tablename], owner, schema, **kw
)[schema, tablename]
def has_multi_table(self, connection, table_names, schema=None, **kw):
# this does not really matche the signature of _db_plus_owner_multi
# so manually do the unpacking here
dbname, owner = _owner_plus_db(self, schema)
return _switch_db(
dbname,
connection,
self._internal_has_multi_table,
connection,
table_names,
owner,
schema,
**kw,
).items()
@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
def _internal_has_multi_table(
self, connection, table_names, owner, schema, **kw
):
regular_names, multi_object_names, temp_names = (
self._partition_filter_names(
connection, owner, table_names, ObjectScope.ANY, ObjectKind.ANY
)
)
result = {}
if multi_object_names:
# in multi_object_names we already have the names that exist in
# the database, no need to do another query here
name_map = self._multi_name_map(regular_names)
for server_name in multi_object_names:
result[(schema, name_map(server_name))] = True
if temp_names:
# mssql does not support temporary views
# U filters on user tables only.
query = text("SELECT object_id(:table_name, 'U')")
for temp_name in temp_names:
result[(schema, temp_name)] = bool(
connection.scalar(
query,
{"table_name": f"tempdb..[{temp_name}]"},
)
)
for name in table_names:
result.setdefault((schema, name), False)
return result
@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}")
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
def _parse_column_info(
self,
name,
type_,
nullable,
maxlen,
numericprec,
numericscale,
default,
collation,
definition,
is_persisted,
is_identity,
identity_start,
identity_increment,
comment,
base_type=None,
):
# Try to resolve the user type first (e.g., "sysname"),
# then fall back to the base type (e.g., "nvarchar").
# base_type may be None for CLR types (geography, geometry,
# hierarchyid) which have no corresponding base type.
coltype = self.ischema_names.get(type_, None)
if coltype is None and base_type is not None and base_type != type_:
coltype = self.ischema_names.get(base_type, None)
kwargs = {}
if coltype in (MSBinary, MSVarBinary, sqltypes.LargeBinary):
kwargs["length"] = maxlen if maxlen != -1 else None
elif coltype in (MSString, MSChar):
kwargs["length"] = maxlen if maxlen != -1 else None
if collation:
kwargs["collation"] = collation
elif coltype in (MSNVarchar, MSNChar):
kwargs["length"] = maxlen // 2 if maxlen != -1 else None
if collation:
kwargs["collation"] = collation
elif coltype in (MSText, MSNText):
# TEXT / NTEXT are unlengthed LOB types. sys.columns.max_length
# reports 16 for these, which is the size of the in-row LOB
# pointer and not a character length, so no length is applied.
if collation:
kwargs["collation"] = collation
if coltype is None:
if base_type is not None and base_type != type_:
util.warn(
"Did not recognize type '%s' (user type) or '%s' "
"(base type) of column '%s'" % (type_, base_type, name)
)
else:
util.warn(
"Did not recognize type '%s' of column '%s'"
% (type_, name)
)
coltype = sqltypes.NULLTYPE
else:
if issubclass(coltype, sqltypes.NumericCommon):
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:
if identity_start is None or identity_increment is None:
cdict["identity"] = {}
else:
if isinstance(
coltype, (sqltypes.BigInteger, sqltypes.Integer)
):
start = int(identity_start)
increment = int(identity_increment)
else:
start = identity_start
increment = identity_increment
cdict["identity"] = {
"start": start,
"increment": increment,
}
return cdict
@lru_cache()
def _columns_select(self):
"""Build the unified Core sys.* select for column reflection.
Returns a ``select()`` that includes ``table_name`` and ``owner``
in the result so callers can group rows by table.
Used by :meth:`.get_multi_columns` (and indirectly by
:meth:`.get_columns` via the multi delegation).
"""
sys_columns = ischema.sys_columns
sys_types = ischema.sys_types
sys_base_types = ischema.sys_types.alias("base_types")
sys_default_constraints = ischema.sys_default_constraints
computed_cols = ischema.computed_columns
identity_cols = ischema.identity_columns
extended_properties = ischema.extended_properties
sys_objects = ischema.sys_objects
sys_schemas = ischema.sys_schemas
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)
)
s = (
sql.select(
sys_objects.c.name.label("table_name"),
sys_schemas.c.name.label("owner"),
sys_columns.c.name.label("column_name"),
sys_types.c.name.label("type_name"),
sys_base_types.c.name.label("base_type"),
sys_columns.c.is_nullable,
sys_columns.c.max_length,
sys_columns.c.precision,
sys_columns.c.scale,
sys_default_constraints.c.definition.label("default_value"),
sys_columns.c.collation_name,
computed_definition.label("computed_definition"),
computed_cols.c.is_persisted,
identity_cols.c.is_identity,
identity_cols.c.seed_value,
identity_cols.c.increment_value,
extended_properties.c.value.label("comment"),
sys_columns.c.column_id,
)
.select_from(sys_columns)
.join(
sys_objects,
onclause=sys_columns.c.object_id == sys_objects.c.object_id,
)
.join(
sys_schemas,
onclause=sys_objects.c.schema_id == sys_schemas.c.schema_id,
)
.join(
sys_types,
onclause=sys_columns.c.user_type_id
== sys_types.c.user_type_id,
)
.outerjoin(
sys_base_types,
onclause=sql.and_(
sys_types.c.system_type_id
== sys_base_types.c.system_type_id,
sys_base_types.c.user_type_id
== sys_base_types.c.system_type_id,
),
)
.outerjoin(
sys_default_constraints,
sql.and_(
sys_default_constraints.c.object_id
== sys_columns.c.default_object_id,
sys_default_constraints.c.parent_column_id
== sys_columns.c.column_id,
),
)
.outerjoin(
computed_cols,
onclause=sql.and_(
computed_cols.c.object_id == sys_columns.c.object_id,
computed_cols.c.column_id == sys_columns.c.column_id,
),
)
.outerjoin(
identity_cols,
onclause=sql.and_(
identity_cols.c.object_id == sys_columns.c.object_id,
identity_cols.c.column_id == sys_columns.c.column_id,
),
)
.outerjoin(
extended_properties,
onclause=sql.and_(
extended_properties.c["class"] == 1,
extended_properties.c.name == "MS_Description",
sys_columns.c.object_id == extended_properties.c.major_id,
sys_columns.c.column_id == extended_properties.c.minor_id,
),
)
.where(
ischema.sys_schemas.c.name == sql.bindparam("owner"),
ischema.sys_objects.c.name.in_(
sql.bindparam("filter_names", expanding=True)
),
)
.order_by(sys_objects.c.name, sys_columns.c.column_id)
)
return s
@staticmethod
def _fk_query_sql(fk_info_where, extra_cols=""):
return """\
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 %(fk_info_where)s
),
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
%(extra_cols)s
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
%(extra_cols)s
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
AND NOT (index_info.table_schema = fk_info.table_schema
AND index_info.table_name = fk_info.table_name)
ORDER BY fk_info.constraint_schema, fk_info.constraint_name,
fk_info.ordinal_position
""" % {
"fk_info_where": fk_info_where,
"extra_cols": extra_cols,
}
# --- multi-reflection API ---
@lru_cache
def _partition_filter_names_query(self, add_filter_names: bool):
sys_objects = ischema.sys_objects
sys_schemas = ischema.sys_schemas
s = (
sql.select(sys_objects.c.name)
.select_from(sys_objects)
.join(
sys_schemas,
onclause=sys_objects.c.schema_id == sys_schemas.c.schema_id,
)
.where(
sys_schemas.c.name == sql.bindparam("schema"),
sys_objects.c.type.in_(
sql.bindparam("type_filter", expanding=True)
),
)
)
if add_filter_names:
s = s.where(
sys_objects.c.name.in_(
sql.bindparam("filter_names", expanding=True)
)
)
return s
def _partition_filter_names(
self, connection, owner, filter_names, scope, kind
):
"""Split caller-supplied ``filter_names`` between the bulk
``sys.*`` query path (regular objects in the user database) and
the temp object path (objects living in ``tempdb``), and resolve
the existing-in-catalog names for the bulk path in one shot.
Returns the tuple
``(regular_names, multi_object_names, temp_names)``:
* ``regular_names`` -- list of caller-supplied names (with the
caller's casing) for the bulk path, used to build the
case-insensitive name map. Empty list when no regular names
were requested.
* ``multi_object_names`` -- list of names (with server-side
casing) that actually exist in the catalog and match the
requested ``kind``. This is what the bulk SQL's IN clause
gets filtered with. Empty list when no matches, disabling
the bulk query.
* ``temp_names`` -- list of ``#``-prefixed temp object names
that the caller asked for and that the requested
``scope``/``kind`` allows.
``scope=ObjectScope.DEFAULT`` excludes temp objects entirely.
``scope=ObjectScope.TEMPORARY`` excludes regular objects.
``ObjectKind.VIEW`` (without TABLE) excludes temp because SQL
Server does not have temp views in the same form. SQL Server
also has no ``get_temp_table_names`` implementation, so temp
objects can only be reflected when the caller supplies their
names explicitly.
"""
include_default = scope is not ObjectScope.TEMPORARY
include_temp = (
scope is not ObjectScope.DEFAULT and ObjectKind.TABLE in kind
)
if filter_names:
if include_temp:
temp_names = [n for n in filter_names if n.startswith("#")]
else:
temp_names = []
if include_default:
regular_names = [
n for n in filter_names if not n.startswith("#")
]
run_bulk = bool(regular_names)
else:
regular_names = []
run_bulk = False
else:
temp_names = []
regular_names = []
run_bulk = include_default
if not run_bulk:
return (regular_names, [], temp_names)
type_filter = []
if ObjectKind.TABLE in kind:
type_filter.append("U")
if ObjectKind.VIEW in kind:
type_filter.append("V")
# SQL Server does not support materialized views, so ignore them
if not type_filter:
return (regular_names, [], temp_names)
has_regular_names = bool(regular_names)
query = self._partition_filter_names_query(has_regular_names)
params = {"schema": owner, "type_filter": type_filter}
if has_regular_names:
params["filter_names"] = regular_names
multi_object_names = connection.scalars(query, params).all()
return (regular_names, multi_object_names, temp_names)
@staticmethod
def _multi_name_map(filter_names):
"""Build a case-insensitive ``server_name -> user_name`` mapper.
MSSQL object names are case-insensitive under the default
collation, so a user may pass ``"sOmEtAbLe"`` for a table
physically stored as ``"SomeTable"``. The bulk SQL returns the
server-side casing, but result keys must use the user-supplied
casing so that downstream code (e.g.
:meth:`.Inspector.reflect_table`) can find the entry.
Returns a callable ``(server_name) -> user_name``. When
``filter_names`` is empty/None, returns identity.
"""
if not filter_names:
return lambda n: n
lookup = {n.lower(): n for n in filter_names}
return lambda n: lookup.get(n.lower(), n)
@_db_plus_owner_multi
def get_multi_columns(
self,
connection,
dbname,
owner,
schema,
filter_names,
scope,
kind,
**kw,
):
regular_names, multi_object_names, temp_names = (
self._partition_filter_names(
connection, owner, filter_names, scope, kind
)
)
result = {}
if multi_object_names:
name_map = self._multi_name_map(regular_names)
self._fetch_multi_columns(
connection,
owner=owner,
names=multi_object_names,
schema=schema,
name_map=name_map,
result=result,
exec_opts={"schema_translate_map": {}},
)
if temp_names:
self._fetch_multi_columns_temp(
connection,
temp_names=temp_names,
schema=schema,
result=result,
)
return result.items()
def _fetch_multi_columns(
self, connection, owner, names, schema, name_map, result, exec_opts
):
"""Execute the unified columns select for a single catalog pass.
Used by :meth:`.get_multi_columns` for both the main-database pass
(no ``schema_translate_map``) and the tempdb pass (with
``schema_translate_map={"sys": "tempdb.sys"}`` applied).
"""
s = self._columns_select()
rp = connection.execute(
s,
{"owner": owner, "filter_names": names},
execution_options=exec_opts,
)
for row in rp.mappings():
table_name = name_map(row["table_name"])
cdict = self._parse_column_info(
name=row["column_name"],
type_=row["type_name"],
base_type=row["base_type"],
nullable=row["is_nullable"] == 1,
maxlen=row["max_length"],
numericprec=row["precision"],
numericscale=row["scale"],
default=row["default_value"],
collation=row["collation_name"],
definition=row["computed_definition"],
is_persisted=row["is_persisted"],
is_identity=row["is_identity"],
identity_start=row["seed_value"],
identity_increment=row["increment_value"],
comment=row["comment"],
)
result.setdefault((schema, table_name), []).append(cdict)
for n in names:
key = (schema, name_map(n))
if key not in result:
result[key] = ReflectionDefaults.columns()
def _fetch_multi_columns_temp(
self, connection, temp_names, schema, result
):
"""Run the unified columns select against tempdb for temp names.
Resolves each ``#name`` to its mangled tempdb name (one round
trip per temp via :meth:`._get_internal_temp_table_name`), then
runs a single bulk select against ``tempdb.sys.*`` via
``schema_translate_map``. The result rows (keyed by mangled
name) are mapped back to the original ``#name`` for the caller.
"""
resolved_by_owner, temp_name_map = self._resolve_temp_names(
connection, temp_names
)
for temp_owner, mangled_names in resolved_by_owner.items():
self._fetch_multi_columns(
connection,
owner=temp_owner,
names=mangled_names,
schema=schema,
name_map=temp_name_map,
result=result,
exec_opts={"schema_translate_map": {"sys": "tempdb.sys"}},
)
def _resolve_temp_names(self, connection, temp_names):
"""Resolve user-facing temp names (``#foo``) to their mangled
tempdb names, grouped by owner.
Returns ``(resolved_by_owner, temp_name_map)``:
* ``resolved_by_owner`` -- ``{owner: [mangled_name, ...]}``,
one bulk query per owner (typically just ``'dbo'``).
* ``temp_name_map`` -- a function that maps mangled names back
to the user-supplied name.
Names that don't resolve (no matching temp table in tempdb) are
silently dropped. The single-table reflection wrappers handle
the resulting absence by raising :exc:`.NoSuchTableError` via
:meth:`._value_or_raise`.
"""
resolved_by_owner = {}
original_by_mangled = {}
for name in temp_names:
try:
temp_owner, mangled = self._get_internal_temp_table_name(
connection, name
)
except exc.NoSuchTableError:
continue
resolved_by_owner.setdefault(temp_owner, []).append(mangled)
original_by_mangled[mangled] = name
def temp_name_map(server_name):
return original_by_mangled.get(server_name, server_name)
return resolved_by_owner, temp_name_map
@_db_plus_owner_multi
def get_multi_pk_constraint(
self,
connection,
dbname,
owner,
schema,
filter_names,
scope,
kind,
**kw,
):
regular_names, multi_object_names, temp_names = (
self._partition_filter_names(
connection, owner, filter_names, scope, kind
)
)
result = {}
if multi_object_names:
name_map = self._multi_name_map(regular_names)
self._fetch_multi_pk_constraint(
connection,
owner=owner,
names=multi_object_names,
schema=schema,
name_map=name_map,
result=result,
exec_opts={"schema_translate_map": {}},
)
if temp_names:
self._fetch_multi_pk_constraint_temp(
connection,
temp_names=temp_names,
schema=schema,
result=result,
)
return result.items()
@lru_cache()
def _pk_constraint_select(self):
"""Build the unified Core sys.* select for PK constraint reflection.
Returns a ``select()`` that includes ``table_name`` and ``owner``
in the result so callers can group rows by table. The clustered
flag comes directly from ``sys.indexes.type`` (1 = clustered).
"""
sys_key_constraints = ischema.sys_key_constraints
sys_indexes = ischema.sys_indexes
sys_index_columns = ischema.sys_index_columns
sys_columns = ischema.sys_columns
sys_objects = ischema.sys_objects
sys_schemas = ischema.sys_schemas
s = (
sql.select(
sys_objects.c.name.label("table_name"),
sys_schemas.c.name.label("owner"),
sys_key_constraints.c.name.label("constraint_name"),
sys_columns.c.name.label("column_name"),
sys_index_columns.c.key_ordinal,
sys_indexes.c.type.label("index_type"),
)
.select_from(sys_key_constraints)
.join(
sys_objects,
onclause=sys_key_constraints.c.parent_object_id
== sys_objects.c.object_id,
)
.join(
sys_schemas,
onclause=sys_objects.c.schema_id == sys_schemas.c.schema_id,
)
.join(
sys_index_columns,
onclause=sql.and_(
sys_index_columns.c.object_id
== sys_key_constraints.c.parent_object_id,
sys_index_columns.c.index_id
== sys_key_constraints.c.unique_index_id,
),
)
.join(
sys_columns,
onclause=sql.and_(
sys_columns.c.object_id == sys_index_columns.c.object_id,
sys_columns.c.column_id == sys_index_columns.c.column_id,
),
)
.join(
sys_indexes,
onclause=sql.and_(
sys_indexes.c.object_id
== sys_key_constraints.c.parent_object_id,
sys_indexes.c.index_id
== sys_key_constraints.c.unique_index_id,
),
)
.where(
sys_key_constraints.c.type == "PK",
ischema.sys_schemas.c.name == sql.bindparam("owner"),
ischema.sys_objects.c.name.in_(
sql.bindparam("filter_names", expanding=True)
),
)
.order_by(sys_objects.c.name, sys_index_columns.c.key_ordinal)
)
return s
def _fetch_multi_pk_constraint(
self, connection, owner, names, schema, name_map, result, exec_opts
):
"""Execute the unified pk_constraint select for one catalog pass.
Used by :meth:`.get_multi_pk_constraint` for both the main DB
pass and the tempdb pass (with ``schema_translate_map`` set).
"""
s = self._pk_constraint_select()
rp = connection.execute(
s,
{"owner": owner, "filter_names": names},
execution_options=exec_opts,
)
for row in rp.mappings():
table_name = name_map(row["table_name"])
key = (schema, table_name)
if key not in result:
result[key] = {
"constrained_columns": [],
"name": row["constraint_name"],
"dialect_options": {
"mssql_clustered": row["index_type"] == 1
},
}
result[key]["constrained_columns"].append(row["column_name"])
for n in names:
key = (schema, name_map(n))
if key not in result:
result[key] = ReflectionDefaults.pk_constraint()
def _fetch_multi_pk_constraint_temp(
self, connection, temp_names, schema, result
):
"""Run the unified pk_constraint select against tempdb."""
resolved_by_owner, temp_name_map = self._resolve_temp_names(
connection, temp_names
)
for temp_owner, mangled_names in resolved_by_owner.items():
self._fetch_multi_pk_constraint(
connection,
owner=temp_owner,
names=mangled_names,
schema=schema,
name_map=temp_name_map,
result=result,
exec_opts={"schema_translate_map": {"sys": "tempdb.sys"}},
)
@_db_plus_owner_multi
def get_multi_foreign_keys(
self,
connection,
dbname,
owner,
schema,
filter_names,
scope,
kind,
**kw,
):
regular_names, multi_object_names, temp_names = (
self._partition_filter_names(
connection, owner, filter_names, scope, kind
)
)
final = {}
if multi_object_names:
name_map = self._multi_name_map(regular_names)
self._fetch_multi_foreign_keys(
connection,
dbname=dbname,
owner=owner,
names=multi_object_names,
schema=schema,
name_map=name_map,
final=final,
)
# FK reflection for temp tables: the INFORMATION_SCHEMA query in
# _fk_query_sql does not see tempdb objects (it queries the main
# DB's catalog). The pre-existing single-table behavior was to
# return empty foreign_keys for temp tables that exist. We
# preserve that here by checking existence and returning the
# default (empty) reflection for each temp that is reachable.
has_temp_tables = self._internal_has_multi_table(
connection, temp_names, owner="dbo", schema=schema, **kw
)
for name in temp_names:
key = (schema, name)
if has_temp_tables.get(key):
final[key] = ReflectionDefaults.foreign_keys()
return final.items()
def _fetch_multi_foreign_keys(
self, connection, dbname, owner, names, schema, name_map, final
):
"""Execute the unified FK query for the main-DB pass.
Uses the _fk_query_sql sql text, restricted to the provided owner and
IN-list of names. Groups result rows by table and constraint
name into the final dict.
"""
rp = connection.execute(
sql.text(
self._fk_query_sql(
fk_info_where=(
"ischema_key_col.table_schema = :owner"
"\n AND ischema_key_col.table_name"
" IN :filter_names"
),
extra_cols="fk_info.table_name,",
)
)
.bindparams(
sql.bindparam("owner", owner, ischema.CoerceUnicode()),
sql.bindparam("filter_names", names, expanding=True),
)
.columns(
constraint_schema=sqltypes.Unicode(),
constraint_name=sqltypes.Unicode(),
table_name=sqltypes.Unicode(),
constrained_column=sqltypes.Unicode(),
referred_table_schema=sqltypes.Unicode(),
referred_table_name=sqltypes.Unicode(),
referred_column=sqltypes.Unicode(),
)
)
grouped = {}
for r in rp.all():
(
table_name,
_, # constraint_schema
rfknm,
_, # ordinal
scol,
rschema,
rtbl,
rcol,
_, # match
fkuprule,
fkdelrule,
) = r
key = (schema, name_map(table_name))
if key not in grouped:
grouped[key] = util.defaultdict(
lambda: {
"name": None,
"constrained_columns": [],
"referred_schema": None,
"referred_table": None,
"referred_columns": [],
"options": {},
}
)
rec = grouped[key][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
rec["constrained_columns"].append(scol)
rec["referred_columns"].append(rcol)
for key, fk_dict in grouped.items():
final[key] = list(fk_dict.values())
for n in names:
key = (schema, name_map(n))
if key not in final:
final[key] = ReflectionDefaults.foreign_keys()
@_db_plus_owner_multi
def get_multi_indexes(
self,
connection,
dbname,
owner,
schema,
filter_names,
scope,
kind,
**kw,
):
regular_names, multi_object_names, temp_names = (
self._partition_filter_names(
connection, owner, filter_names, scope, kind
)
)
result = {}
if multi_object_names:
name_map = self._multi_name_map(regular_names)
self._fetch_multi_indexes(
connection,
owner=owner,
names=multi_object_names,
schema=schema,
name_map=name_map,
result=result,
exec_opts={"schema_translate_map": {}},
)
if temp_names:
self._fetch_multi_indexes_temp(
connection,
temp_names=temp_names,
schema=schema,
result=result,
)
return result.items()
@lru_cache()
def _indexes_metadata_select(self):
"""Build the Core sys.* select for index metadata (one row per
index per table).
Used by :meth:`._fetch_multi_indexes` for both the main-DB pass
and the tempdb pass (via ``schema_translate_map``). Replaces a
previous ``sql.text()`` body that did not honor
``schema_translate_map`` (which only rewrites Core
schema-bearing objects, not literal SQL text).
"""
sys_indexes = ischema.sys_indexes
sys_objects = ischema.sys_objects
sys_schemas = ischema.sys_schemas
if self.server_version_info >= MS_2008_VERSION:
filter_definition = sys_indexes.c.filter_definition
else:
filter_definition = sql.null()
s = (
sql.select(
sys_objects.c.name.label("table_name"),
sys_indexes.c.index_id,
sys_indexes.c.is_unique,
sys_indexes.c.name,
sys_indexes.c.type,
filter_definition.label("filter_definition"),
)
.select_from(sys_indexes)
.join(
sys_objects,
onclause=sys_indexes.c.object_id == sys_objects.c.object_id,
)
.join(
sys_schemas,
onclause=sys_schemas.c.schema_id == sys_objects.c.schema_id,
)
.where(
sys_indexes.c.is_primary_key == 0,
sys_indexes.c.type != 0,
ischema.sys_schemas.c.name == sql.bindparam("owner"),
ischema.sys_objects.c.name.in_(
sql.bindparam("filter_names", expanding=True)
),
)
.order_by(sys_objects.c.name, sys_indexes.c.name)
)
return s
@lru_cache()
def _indexes_columns_select(self):
"""Build the Core sys.* select for index columns (one row per
index column per index per table)."""
sys_index_columns = ischema.sys_index_columns
sys_columns = ischema.sys_columns
sys_objects = ischema.sys_objects
sys_schemas = ischema.sys_schemas
s = (
sql.select(
sys_objects.c.name.label("table_name"),
sys_index_columns.c.index_id,
sys_columns.c.name,
sys_index_columns.c.is_included_column,
)
.select_from(sys_index_columns)
.join(
sys_columns,
onclause=sql.and_(
sys_columns.c.object_id == sys_index_columns.c.object_id,
sys_columns.c.column_id == sys_index_columns.c.column_id,
),
)
.join(
sys_objects,
onclause=sys_objects.c.object_id
== sys_index_columns.c.object_id,
)
.join(
sys_schemas,
onclause=sys_schemas.c.schema_id == sys_objects.c.schema_id,
)
.where(
ischema.sys_schemas.c.name == sql.bindparam("owner"),
ischema.sys_objects.c.name.in_(
sql.bindparam("filter_names", expanding=True)
),
)
.order_by(
sys_objects.c.name,
sys_index_columns.c.index_id,
sys_index_columns.c.key_ordinal,
)
)
return s
def _fetch_multi_indexes(
self, connection, owner, names, schema, name_map, result, exec_opts
):
"""Execute the unified indexes queries for one catalog pass.
Runs two Core sys.* selects (index metadata + index columns),
grouped by table. Used for both the main-DB pass and the
tempdb pass (with ``schema_translate_map={"sys": "tempdb.sys"}``
applied).
"""
meta_q = self._indexes_metadata_select()
rp = connection.execute(
meta_q,
{"owner": owner, "filter_names": names},
execution_options=exec_opts,
)
# {table_name: {index_id: index_dict}}
indexes_by_table = {}
for row in rp.mappings():
tname = name_map(row["table_name"])
if tname not in indexes_by_table:
indexes_by_table[tname] = {}
current = {
"name": row["name"],
"unique": row["is_unique"] == 1,
"column_names": [],
"dialect_options": {"mssql_include": []},
}
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"]
indexes_by_table[tname][row["index_id"]] = current
cols_q = self._indexes_columns_select()
rp2 = connection.execute(
cols_q,
{"owner": owner, "filter_names": names},
execution_options=exec_opts,
)
for row in rp2.mappings():
tname = name_map(row["table_name"])
idx_id = row["index_id"]
if tname not in indexes_by_table:
continue
if idx_id not in indexes_by_table[tname]:
continue
index_def = indexes_by_table[tname][idx_id]
do = index_def["dialect_options"]
is_colstore = do.get("mssql_columnstore")
is_clustered = do.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
do["mssql_include"].append(row["name"])
else:
index_def["column_names"].append(row["name"])
for tname, idx_dict in indexes_by_table.items():
result[(schema, tname)] = list(idx_dict.values())
for n in names:
key = (schema, name_map(n))
if key not in result:
result[key] = ReflectionDefaults.indexes()
def _fetch_multi_indexes_temp(
self, connection, temp_names, schema, result
):
"""Run the unified indexes queries against tempdb."""
resolved_by_owner, temp_name_map = self._resolve_temp_names(
connection, temp_names
)
for temp_owner, mangled_names in resolved_by_owner.items():
self._fetch_multi_indexes(
connection,
owner=temp_owner,
names=mangled_names,
schema=schema,
name_map=temp_name_map,
result=result,
exec_opts={"schema_translate_map": {"sys": "tempdb.sys"}},
)
@_db_plus_owner_multi
def get_multi_table_comment(
self,
connection,
dbname,
owner,
schema,
filter_names,
scope,
kind,
**kw,
):
if not self.supports_comments:
raise NotImplementedError(
"Can't get table comments on current SQL Server "
"version in use"
)
regular_names, multi_object_names, temp_names = (
self._partition_filter_names(
connection, owner, filter_names, scope, kind
)
)
result = {}
if multi_object_names:
name_map = self._multi_name_map(regular_names)
self._fetch_multi_table_comment(
connection,
owner=owner,
names=multi_object_names,
schema=schema,
name_map=name_map,
result=result,
exec_opts={"schema_translate_map": {}},
)
if temp_names:
self._fetch_multi_table_comment_temp(
connection,
temp_names=temp_names,
schema=schema,
result=result,
)
return result.items()
@lru_cache()
def _table_comment_select(self):
"""Build the Core sys.* select for table comment reflection."""
sys_objects = ischema.sys_objects
sys_schemas = ischema.sys_schemas
extended_properties = ischema.extended_properties
s = (
sql.select(
sys_objects.c.name.label("table_name"),
extended_properties.c.value.label("comment"),
)
.select_from(sys_objects)
.join(
sys_schemas,
onclause=sys_objects.c.schema_id == sys_schemas.c.schema_id,
)
.outerjoin(
extended_properties,
onclause=sql.and_(
extended_properties.c["class"] == 1,
extended_properties.c.name == "MS_Description",
extended_properties.c.major_id == sys_objects.c.object_id,
extended_properties.c.minor_id == 0,
),
)
.where(
sys_objects.c.type.in_(("U", "V")),
ischema.sys_schemas.c.name == sql.bindparam("owner"),
ischema.sys_objects.c.name.in_(
sql.bindparam("filter_names", expanding=True)
),
)
)
return s
def _fetch_multi_table_comment(
self, connection, owner, names, schema, name_map, result, exec_opts
):
"""Execute the unified table comment query for one catalog pass.
Core sys.* select so ``schema_translate_map`` actually rewrites
the catalog reference for the tempdb pass.
"""
q = self._table_comment_select()
rp = connection.execute(
q,
{"owner": owner, "filter_names": names},
execution_options=exec_opts,
)
for row in rp.mappings():
table_name = name_map(row["table_name"])
comment = row["comment"]
result[(schema, table_name)] = (
{"text": comment} if comment else {"text": None}
)
for n in names:
key = (schema, name_map(n))
if key not in result:
result[key] = ReflectionDefaults.table_comment()
def _fetch_multi_table_comment_temp(
self, connection, temp_names, schema, result
):
"""Run the unified table comment query against tempdb."""
resolved_by_owner, temp_name_map = self._resolve_temp_names(
connection, temp_names
)
for temp_owner, mangled_names in resolved_by_owner.items():
self._fetch_multi_table_comment(
connection,
owner=temp_owner,
names=mangled_names,
schema=schema,
name_map=temp_name_map,
result=result,
exec_opts={"schema_translate_map": {"sys": "tempdb.sys"}},
)
# override mixin methods for which this dialect has no native
# get_multi_* implementation, preventing infinite recursion
# through DefaultDialect._default_multi_reflect
def get_unique_constraints(
self, connection, table_name, schema=None, **kw
):
raise NotImplementedError()
def get_check_constraints(self, connection, table_name, schema=None, **kw):
raise NotImplementedError()
def get_table_options(self, connection, table_name, schema=None, **kw):
raise NotImplementedError()