SQLAlchemy 0.7 Documentation

Release: 0.7.10 | Release Date: February 7, 2013
SQLAlchemy 0.7 Documentation » Dialects » Microsoft SQL Server

Microsoft SQL Server

Microsoft SQL Server

Support for the Microsoft SQL Server database.

Connecting

See the individual driver sections below for details on connecting.

Auto Increment Behavior

IDENTITY columns are supported by using SQLAlchemy schema.Sequence() objects. In other words:

from sqlalchemy import Table, Integer, Sequence, Column

Table('test', metadata,
       Column('id', Integer,
              Sequence('blah',100,10), primary_key=True),
       Column('name', String(20))
     ).create(some_engine)

would yield:

CREATE TABLE test (
  id INTEGER NOT NULL IDENTITY(100,10) PRIMARY KEY,
  name VARCHAR(20) NULL,
  )

Note that the start and increment values for sequences are optional and will default to 1,1.

Implicit autoincrement behavior works the same in MSSQL as it does in other dialects and results in an IDENTITY column.

  • Support for SET IDENTITY_INSERT ON mode (automagic on / off for INSERT s)
  • Support for auto-fetching of @@IDENTITY/@@SCOPE_IDENTITY() on INSERT

Collation Support

MSSQL specific string types support a collation parameter that creates a column-level specific collation for the column. The collation parameter accepts a Windows Collation Name or a SQL Collation Name. Supported types are MSChar, MSNChar, MSString, MSNVarchar, MSText, and MSNText. For example:

from sqlalchemy.dialects.mssql import VARCHAR
Column('login', VARCHAR(32, collation='Latin1_General_CI_AS'))

When such a column is associated with a Table, the CREATE TABLE statement for this column will yield:

login VARCHAR(32) COLLATE Latin1_General_CI_AS NULL

LIMIT/OFFSET Support

MSSQL has no support for the LIMIT or OFFSET keysowrds. LIMIT is supported directly through the TOP Transact SQL keyword:

select.limit

will yield:

SELECT TOP n

If using SQL Server 2005 or above, LIMIT with OFFSET support is available through the ROW_NUMBER OVER construct. For versions below 2005, LIMIT with OFFSET usage will fail.

Nullability

MSSQL has support for three levels of column nullability. The default nullability allows nulls and is explicit in the CREATE TABLE construct:

name VARCHAR(20) NULL

If nullable=None is specified then no specification is made. In other words the database’s configured default is used. This will render:

name VARCHAR(20)

If nullable is True or False then the column will be NULL` or ``NOT NULL respectively.

Date / Time Handling

DATE and TIME are supported. Bind parameters are converted to datetime.datetime() objects as required by most MSSQL drivers, and results are processed from strings if needed. The DATE and TIME types are not available for MSSQL 2005 and previous - if a server version below 2008 is detected, DDL for these types will be issued as DATETIME.

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 SQAlchemy may attempt to use T-SQL statements that are unable to be parsed by the database server.

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 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}

This option can also be specified engine-wide using the implicit_returning=False argument on create_engine().

Enabling Snapshot Isolation

Not necessarily specific to SQLAlchemy, SQL Server has a default transaction isolation mode that locks entire tables, and causes even mildly concurrent applications to have long held locks and frequent deadlocks. Enabling snapshot isolation for the database as a whole is recommended for modern levels of concurrency support. This is accomplished via the following ALTER DATABASE commands executed at the SQL prompt:

ALTER DATABASE MyDatabase SET ALLOW_SNAPSHOT_ISOLATION ON

ALTER DATABASE MyDatabase SET READ_COMMITTED_SNAPSHOT ON

Background on SQL Server snapshot isolation is available at http://msdn.microsoft.com/en-us/library/ms175095.aspx.

Scalar Select Comparisons

Deprecated since version 0.8: The MSSQL dialect contains a legacy behavior whereby comparing a scalar select to a value using the = or != operator will resolve to IN or NOT IN, respectively. This behavior will be removed in 0.8 - the s.in_()/~s.in_() operators should be used when IN/NOT IN are desired.

For the time being, the existing behavior prevents a comparison between scalar select and another value that actually wants to use =. To remove this behavior in a forwards-compatible way, apply this compilation rule by placing the following code at the module import level:

from sqlalchemy.ext.compiler import compiles
from sqlalchemy.sql.expression import _BinaryExpression
from sqlalchemy.sql.compiler import SQLCompiler

@compiles(_BinaryExpression, 'mssql')
def override_legacy_binary(element, compiler, **kw):
    return SQLCompiler.visit_binary(compiler, element, **kw)

Known Issues

  • No support for more than one IDENTITY column per table
  • reflection of indexes does not work with versions older than SQL Server 2005

SQL Server Data Types

As with all SQLAlchemy dialects, all UPPERCASE types that are known to be valid with SQL server are importable from the top level dialect, whether they originate from sqlalchemy.types or from the local dialect:

from sqlalchemy.dialects.mssql import \
    BIGINT, BINARY, BIT, CHAR, DATE, DATETIME, DATETIME2, \
    DATETIMEOFFSET, DECIMAL, FLOAT, IMAGE, INTEGER, MONEY, \
    NCHAR, NTEXT, NUMERIC, NVARCHAR, REAL, SMALLDATETIME, \
    SMALLINT, SMALLMONEY, SQL_VARIANT, TEXT, TIME, \
    TIMESTAMP, TINYINT, UNIQUEIDENTIFIER, VARBINARY, VARCHAR

Types which are specific to SQL Server, or have SQL Server-specific construction arguments, are as follows:

class sqlalchemy.dialects.mssql.BIT(*args, **kwargs)

Bases: sqlalchemy.types.TypeEngine

__init__(*args, **kwargs)

Support implementations that were passing arguments

class sqlalchemy.dialects.mssql.CHAR(length=None, collation=None, **kw)

Bases: sqlalchemy.dialects.mssql.base._StringType, sqlalchemy.types.CHAR

MSSQL CHAR type, for fixed-length non-Unicode data with a maximum of 8,000 characters.

__init__(length=None, collation=None, **kw)

Construct a CHAR.

Parameters:
  • length – Optinal, maximum data length, in characters.
  • convert_unicode

    defaults to False. If True, convert unicode data sent to the database to a str bytestring, and convert bytestrings coming back from the database into unicode.

    Bytestrings are encoded using the dialect’s encoding, which defaults to utf-8.

    If False, may be overridden by sqlalchemy.engine.base.Dialect.convert_unicode.

  • collation – Optional, a column-level collation for this string value. Accepts a Windows Collation Name or a SQL Collation Name.
class sqlalchemy.dialects.mssql.DATETIME2(precision=None, **kw)

Bases: sqlalchemy.dialects.mssql.base._DateTimeBase, sqlalchemy.types.DateTime

class sqlalchemy.dialects.mssql.DATETIMEOFFSET(precision=None, **kwargs)

Bases: sqlalchemy.types.TypeEngine

class sqlalchemy.dialects.mssql.IMAGE(length=None)

Bases: sqlalchemy.types.LargeBinary

__init__(length=None)

Construct a LargeBinary type.

Parameters:length – optional, a length for the column for use in DDL statements, for those BLOB types that accept a length (i.e. MySQL). It does not produce a small BINARY/VARBINARY type - use the BINARY/VARBINARY types specifically for those. May be safely omitted if no CREATE TABLE will be issued. Certain databases may require a length for use in DDL, and will raise an exception when the CREATE TABLE DDL is issued.
class sqlalchemy.dialects.mssql.MONEY(*args, **kwargs)

Bases: sqlalchemy.types.TypeEngine

__init__(*args, **kwargs)

Support implementations that were passing arguments

class sqlalchemy.dialects.mssql.NCHAR(length=None, collation=None, **kw)

Bases: sqlalchemy.dialects.mssql.base._StringType, sqlalchemy.types.NCHAR

MSSQL NCHAR type.

For fixed-length unicode character data up to 4,000 characters.

__init__(length=None, collation=None, **kw)

Construct an NCHAR.

Parameters:
  • length – Optional, Maximum data length, in characters.
  • collation – Optional, a column-level collation for this string value. Accepts a Windows Collation Name or a SQL Collation Name.
class sqlalchemy.dialects.mssql.NTEXT(length=None, collation=None, **kw)

Bases: sqlalchemy.dialects.mssql.base._StringType, sqlalchemy.types.UnicodeText

MSSQL NTEXT type, for variable-length unicode text up to 2^30 characters.

__init__(length=None, collation=None, **kw)

Construct a NTEXT.

Parameters:collation – Optional, a column-level collation for this string value. Accepts a Windows Collation Name or a SQL Collation Name.
class sqlalchemy.dialects.mssql.NVARCHAR(length=None, collation=None, **kw)

Bases: sqlalchemy.dialects.mssql.base._StringType, sqlalchemy.types.NVARCHAR

MSSQL NVARCHAR type.

For variable-length unicode character data up to 4,000 characters.

__init__(length=None, collation=None, **kw)

Construct a NVARCHAR.

Parameters:
  • length – Optional, Maximum data length, in characters.
  • collation – Optional, a column-level collation for this string value. Accepts a Windows Collation Name or a SQL Collation Name.
class sqlalchemy.dialects.mssql.REAL(**kw)

Bases: sqlalchemy.types.REAL

class sqlalchemy.dialects.mssql.SMALLDATETIME(timezone=False)

Bases: sqlalchemy.dialects.mssql.base._DateTimeBase, sqlalchemy.types.DateTime

__init__(timezone=False)

Construct a new DateTime.

Parameters:timezone – boolean. If True, and supported by the

backend, will produce ‘TIMESTAMP WITH TIMEZONE’. For backends that don’t support timezone aware timestamps, has no effect.

class sqlalchemy.dialects.mssql.SMALLMONEY(*args, **kwargs)

Bases: sqlalchemy.types.TypeEngine

__init__(*args, **kwargs)

Support implementations that were passing arguments

class sqlalchemy.dialects.mssql.SQL_VARIANT(*args, **kwargs)

Bases: sqlalchemy.types.TypeEngine

__init__(*args, **kwargs)

Support implementations that were passing arguments

class sqlalchemy.dialects.mssql.TEXT(length=None, collation=None, **kw)

Bases: sqlalchemy.dialects.mssql.base._StringType, sqlalchemy.types.TEXT

MSSQL TEXT type, for variable-length text up to 2^31 characters.

__init__(length=None, collation=None, **kw)

Construct a TEXT.

Parameters:collation – Optional, a column-level collation for this string value. Accepts a Windows Collation Name or a SQL Collation Name.
class sqlalchemy.dialects.mssql.TIME(precision=None, **kwargs)

Bases: sqlalchemy.types.TIME

class sqlalchemy.dialects.mssql.TINYINT(*args, **kwargs)

Bases: sqlalchemy.types.Integer

__init__(*args, **kwargs)

Support implementations that were passing arguments

class sqlalchemy.dialects.mssql.UNIQUEIDENTIFIER(*args, **kwargs)

Bases: sqlalchemy.types.TypeEngine

__init__(*args, **kwargs)

Support implementations that were passing arguments

class sqlalchemy.dialects.mssql.VARCHAR(length=None, collation=None, **kw)

Bases: sqlalchemy.dialects.mssql.base._StringType, sqlalchemy.types.VARCHAR

MSSQL VARCHAR type, for variable-length non-Unicode data with a maximum of 8,000 characters.

__init__(length=None, collation=None, **kw)

Construct a VARCHAR.

Parameters:
  • length – Optinal, maximum data length, in characters.
  • convert_unicode

    defaults to False. If True, convert unicode data sent to the database to a str bytestring, and convert bytestrings coming back from the database into unicode.

    Bytestrings are encoded using the dialect’s encoding, which defaults to utf-8.

    If False, may be overridden by sqlalchemy.engine.base.Dialect.convert_unicode.

  • collation – Optional, a column-level collation for this string value. Accepts a Windows Collation Name or a SQL Collation Name.

PyODBC

Support for MS-SQL via pyodbc.

pyodbc is available at:

Connecting

Examples of pyodbc connection string URLs:

  • mssql+pyodbc://mydsn - connects using the specified DSN named mydsn. The connection string that is created will appear like:

    dsn=mydsn;Trusted_Connection=Yes
  • mssql+pyodbc://user:pass@mydsn - connects using the DSN named mydsn passing in the UID and PWD information. The connection string that is created will appear like:

    dsn=mydsn;UID=user;PWD=pass
  • mssql+pyodbc://user:pass@mydsn/?LANGUAGE=us_english - connects using the DSN named mydsn passing in the UID and PWD information, plus the additional connection configuration option LANGUAGE. The connection string that is created will appear like:

    dsn=mydsn;UID=user;PWD=pass;LANGUAGE=us_english
  • mssql+pyodbc://user:pass@host/db - connects using a connection that would appear like:

    DRIVER={SQL Server};Server=host;Database=db;UID=user;PWD=pass
  • mssql+pyodbc://user:pass@host:123/db - connects using a connection string which includes the port information using the comma syntax. This will create the following connection string:

    DRIVER={SQL Server};Server=host,123;Database=db;UID=user;PWD=pass
  • mssql+pyodbc://user:pass@host/db?port=123 - connects using a connection string that includes the port information as a separate port keyword. This will create the following connection string:

    DRIVER={SQL Server};Server=host;Database=db;UID=user;PWD=pass;port=123
  • mssql+pyodbc://user:pass@host/db?driver=MyDriver - connects using a connection string that includes a custom ODBC driver name. This will create the following connection string:

    DRIVER={MyDriver};Server=host;Database=db;UID=user;PWD=pass

If you require a connection string that is outside the options presented above, use the odbc_connect keyword to pass in a urlencoded connection string. What gets passed in will be urldecoded and passed directly.

For example:

mssql+pyodbc:///?odbc_connect=dsn%3Dmydsn%3BDatabase%3Ddb

would create the following connection string:

dsn=mydsn;Database=db

Encoding your connection string can be easily accomplished through the python shell. For example:

>>> import urllib
>>> urllib.quote_plus('dsn=mydsn;Database=db')
'dsn%3Dmydsn%3BDatabase%3Ddb'

Unicode Binds

The current state of PyODBC on a unix backend with FreeTDS and/or EasySoft is poor regarding unicode; different OS platforms and versions of UnixODBC versus IODBC versus FreeTDS/EasySoft versus PyODBC itself dramatically alter how strings are received. The PyODBC dialect attempts to use all the information it knows to determine whether or not a Python unicode literal can be passed directly to the PyODBC driver or not; while SQLAlchemy can encode these to bytestrings first, some users have reported that PyODBC mis-handles bytestrings for certain encodings and requires a Python unicode object, while the author has observed widespread cases where a Python unicode is completely misinterpreted by PyODBC, particularly when dealing with the information schema tables used in table reflection, and the value must first be encoded to a bytestring.

It is for this reason that whether or not unicode literals for bound parameters be sent to PyODBC can be controlled using the supports_unicode_binds parameter to create_engine(). When left at its default of None, the PyODBC dialect will use its best guess as to whether or not the driver deals with unicode literals well. When False, unicode literals will be encoded first, and when True unicode literals will be passed straight through. This is an interim flag that hopefully should not be needed when the unicode situation stabilizes for unix + PyODBC.

New in version 0.7.7: supports_unicode_binds parameter to create_engine().

mxODBC

Support for MS-SQL via mxODBC.

mxODBC is available at:

This was tested with mxODBC 3.1.2 and the SQL Server Native Client connected to MSSQL 2005 and 2008 Express Editions.

Connecting

Connection is via DSN:

mssql+mxodbc://<username>:<password>@<dsnname>

Execution Modes

mxODBC features two styles of statement execution, using the cursor.execute() and cursor.executedirect() methods (the second being an extension to the DBAPI specification). The former makes use of a particular API call specific to the SQL Server Native Client ODBC driver known SQLDescribeParam, while the latter does not.

mxODBC apparently only makes repeated use of a single prepared statement when SQLDescribeParam is used. The advantage to prepared statement reuse is one of performance. The disadvantage is that SQLDescribeParam has a limited set of scenarios in which bind parameters are understood, including that they cannot be placed within the argument lists of function calls, anywhere outside the FROM, or even within subqueries within the FROM clause - making the usage of bind parameters within SELECT statements impossible for all but the most simplistic statements.

For this reason, the mxODBC dialect uses the “native” mode by default only for INSERT, UPDATE, and DELETE statements, and uses the escaped string mode for all other statements.

This behavior can be controlled via execution_options() using the native_odbc_execute flag with a value of True or False, where a value of True will unconditionally use native bind parameters and a value of False will unconditionally use string-escaped parameters.

pymssql

Support for the pymssql dialect.

This dialect supports pymssql 1.0 and greater.

pymssql is available at:

Connecting

Sample connect string:

mssql+pymssql://<username>:<password>@<freetds_name>

Adding ”?charset=utf8” or similar will cause pymssql to return strings as Python unicode objects. This can potentially improve performance in some scenarios as decoding of strings is handled natively.

Limitations

pymssql inherits a lot of limitations from FreeTDS, including:

  • no support for multibyte schema identifiers
  • poor support for large decimals
  • poor support for binary fields
  • poor support for VARCHAR/CHAR fields over 255 characters

Please consult the pymssql documentation for further information.

zxjdbc Notes

Support for the Microsoft SQL Server database via the zxjdbc JDBC connector.

JDBC Driver

Requires the jTDS driver, available from: http://jtds.sourceforge.net/

Connecting

URLs are of the standard form of mssql+zxjdbc://user:pass@host:port/dbname[?key=value&key=value...].

Additional arguments which may be specified either as query string arguments on the URL, or as keyword arguments to create_engine() will be passed as Connection properties to the underlying JDBC driver.

AdoDBAPI

The adodbapi dialect is not implemented for 0.6 at this time.