Release: 1.0.14 | Release Date: July 6, 2016

# SQLAlchemy 1.0 Documentation

# Column and Data Types

SQLAlchemy provides abstractions for most common database data types, and a mechanism for specifying your own custom data types.

The methods and attributes of type objects are rarely used directly. Type objects are supplied to `Table` definitions and can be supplied as type hints to functions for occasions where the database driver returns an incorrect type.

    >>> users = Table('users', metadata,
    ...               Column('id', Integer, primary_key=True)
    ...               Column('login', String(32))
    ...              )

SQLAlchemy will use the `Integer` and `String(32)` type information when issuing a `CREATE TABLE` statement and will use it again when reading back rows `SELECTed` from the database. Functions that accept a type (such as `Column()`) will typically accept a type class or instance; `Integer` is equivalent to `Integer()` with no construction arguments in this case.

## Generic Types

Generic types specify a column that can read, write and store a particular type of Python data. SQLAlchemy will choose the best database column type available on the target database when issuing a `CREATE TABLE` statement. For complete control over which column type is emitted in `CREATE TABLE`, such as `VARCHAR` see SQL Standard Types and the other sections of this chapter.

class `sqlalchemy.types.``BigInteger`

  Bases: `sqlalchemy.types.Integer`

  A type for bigger `int` integers.

  Typically generates a `BIGINT` in DDL, and otherwise acts like a normal `Integer` on the Python side.

class `sqlalchemy.types.``Boolean`(create_constraint=True, name=None, _create_events=True)

  Bases: `sqlalchemy.types.TypeEngine`, `sqlalchemy.types.SchemaType`

  A bool datatype.

  Boolean typically uses BOOLEAN or SMALLINT on the DDL side, and on the Python side deals in `True` or `False`.

  `__init__`(create_constraint=True, name=None, _create_events=True)

    Construct a Boolean.

    Parameters:

    - create_constraint – defaults to True. If the boolean is generated as an int/smallint, also create a CHECK constraint on the table that ensures 1 or 0 as a value.
    - name – if a CHECK constraint is generated, specify the name of the constraint.

class `sqlalchemy.types.``Date`

  Bases: `sqlalchemy.types._DateAffinity`, `sqlalchemy.types.TypeEngine`

  A type for `datetime.date()` objects.

class `sqlalchemy.types.``DateTime`(timezone=False)

  Bases: `sqlalchemy.types._DateAffinity`, `sqlalchemy.types.TypeEngine`

  A type for `datetime.datetime()` objects.

  Date and time types return objects from the Python `datetime` module. Most DBAPIs have built in support for the datetime module, with the noted exception of SQLite. In the case of SQLite, date and time types are stored as strings which are then converted back to datetime objects when rows are returned.

  `__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.types.``Enum`(*enums, **kw)

  Bases: `sqlalchemy.types.String`, `sqlalchemy.types.SchemaType`

  Generic Enum Type.

  The Enum type provides a set of possible string values which the column is constrained towards.

  By default, uses the backend’s native ENUM type if available, else uses VARCHAR + a CHECK constraint.

  See also

  `ENUM` - PostgreSQL-specific type, which has additional functionality.

  `__init__`(*enums, **kw)

    Construct an enum.

    Keyword arguments which don’t apply to a specific backend are ignored by that backend.

    Parameters:

    - *enums – string or unicode enumeration labels. If unicode labels are present, the convert_unicode flag is auto-enabled.
    - convert_unicode – Enable unicode-aware bind parameter and result-set processing for this Enum’s data. This is set automatically based on the presence of unicode label strings.
    - metadata – Associate this type directly with a `MetaData` object. For types that exist on the target database as an independent schema construct (Postgresql), this type will be created and dropped within `create_all()` and `drop_all()` operations. If the type is not associated with any `MetaData` object, it will associate itself with each `Table` in which it is used, and will be created when any of those individual tables are created, after a check is performed for its existence. The type is only dropped when `drop_all()` is called for that `Table` object’s metadata, however.
    - name – The name of this type. This is required for Postgresql and any future supported database which requires an explicitly named type, or an explicitly named constraint in order to generate the type and/or a table that uses it.
    - native_enum – Use the database’s native ENUM type when available. Defaults to True. When False, uses VARCHAR + check constraint for all backends.
    - schema –

      Schema name of this type. For types that exist on the target database as an independent schema construct (Postgresql), this parameter specifies the named schema in which the type is present.

      Note

      The `schema` of the `Enum` type does not by default make use of the `schema` established on the owning `Table`. If this behavior is desired, set the `inherit_schema` flag to `True`.

    - quote – Set explicit quoting preferences for the type’s name.
    - inherit_schema –

      When `True`, the “schema” from the owning `Table` will be copied to the “schema” attribute of this `Enum`, replacing whatever value was passed for the `schema` attribute. This also takes effect when using the `Table.tometadata()` operation.

      New in version 0.8.

  `create`(bind=None, checkfirst=False)
    inherited from the `create()` method of `SchemaType`

    Issue CREATE ddl for this type, if applicable.

  `drop`(bind=None, checkfirst=False)
    inherited from the `drop()` method of `SchemaType`

    Issue DROP ddl for this type, if applicable.

class `sqlalchemy.types.``Float`(precision=None, asdecimal=False, decimal_return_scale=None, **kwargs)

  Bases: `sqlalchemy.types.Numeric`

  Type representing floating point types, such as `FLOAT` or `REAL`.

  This type returns Python `float` objects by default, unless the `Float.asdecimal` flag is set to True, in which case they are coerced to `decimal.Decimal` objects.

  Note

  The `Float` type is designed to receive data from a database type that is explicitly known to be a floating point type (e.g. `FLOAT`, `REAL`, others) and not a decimal type (e.g. `DECIMAL`, `NUMERIC`, others). If the database column on the server is in fact a Numeric type, such as `DECIMAL` or `NUMERIC`, use the `Numeric` type or a subclass, otherwise numeric coercion between `float`/`Decimal` may or may not function as expected.

  `__init__`(precision=None, asdecimal=False, decimal_return_scale=None, **kwargs)

    Construct a Float.

    Parameters:

    - precision – the numeric precision for use in DDL `CREATE TABLE`.
    - asdecimal – the same flag as that of `Numeric`, but defaults to `False`. Note that setting this flag to `True` results in floating point conversion.
    - decimal_return_scale –

      Default scale to use when converting from floats to Python decimals. Floating point values will typically be much longer due to decimal inaccuracy, and most floating point database types don’t have a notion of “scale”, so by default the float type looks for the first ten decimal places when converting. Specfiying this value will override that length. Note that the MySQL float types, which do include “scale”, will use “scale” as the default for decimal_return_scale, if not otherwise specified.

      New in version 0.9.0.

    - **kwargs – deprecated. Additional arguments here are ignored by the default `Float` type. For database specific floats that support additional arguments, see that dialect’s documentation for details, such as `sqlalchemy.dialects.mysql.FLOAT`.

class `sqlalchemy.types.``Integer`

  Bases: `sqlalchemy.types._DateAffinity`, `sqlalchemy.types.TypeEngine`

  A type for `int` integers.

class `sqlalchemy.types.``Interval`(native=True, second_precision=None, day_precision=None)

  Bases: `sqlalchemy.types._DateAffinity`, `sqlalchemy.types.TypeDecorator`

  A type for `datetime.timedelta()` objects.

  The Interval type deals with `datetime.timedelta` objects. In PostgreSQL, the native `INTERVAL` type is used; for others, the value is stored as a date which is relative to the “epoch” (Jan. 1, 1970).

  Note that the `Interval` type does not currently provide date arithmetic operations on platforms which do not support interval types natively. Such operations usually require transformation of both sides of the expression (such as, conversion of both sides into integer epoch values first) which currently is a manual procedure (such as via `func`).

  `__init__`(native=True, second_precision=None, day_precision=None)

    Construct an Interval object.

    Parameters:

    - native – when True, use the actual INTERVAL type provided by the database, if supported (currently Postgresql, Oracle). Otherwise, represent the interval data as an epoch value regardless.
    - second_precision – For native interval types which support a “fractional seconds precision” parameter, i.e. Oracle and Postgresql
    - day_precision – for native interval types which support a “day precision” parameter, i.e. Oracle.

  `coerce_compared_value`(op, value)

    See `TypeEngine.coerce_compared_value()` for a description.

  `impl`

    alias of `DateTime`

class `sqlalchemy.types.``LargeBinary`(length=None)

  Bases: `sqlalchemy.types._Binary`

  A type for large binary byte data.

  The `LargeBinary` type corresponds to a large and/or unlengthed binary type for the target platform, such as BLOB on MySQL and BYTEA for Postgresql. It also handles the necessary conversions for the DBAPI.

  `__init__`(length=None)

    Construct a LargeBinary type.

    Parameters: | 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.

class `sqlalchemy.types.``MatchType`(create_constraint=True, name=None, _create_events=True)

  Bases: `sqlalchemy.types.Boolean`

  Refers to the return type of the MATCH operator.

  As the `ColumnOperators.match()` is probably the most open-ended operator in generic SQLAlchemy Core, we can’t assume the return type at SQL evaluation time, as MySQL returns a floating point, not a boolean, and other backends might do something different. So this type acts as a placeholder, currently subclassing `Boolean`. The type allows dialects to inject result-processing functionality if needed, and on MySQL will return floating-point values.

  New in version 1.0.0.

class `sqlalchemy.types.``Numeric`(precision=None, scale=None, decimal_return_scale=None, asdecimal=True)

  Bases: `sqlalchemy.types._DateAffinity`, `sqlalchemy.types.TypeEngine`

  A type for fixed precision numbers, such as `NUMERIC` or `DECIMAL`.

  This type returns Python `decimal.Decimal` objects by default, unless the `Numeric.asdecimal` flag is set to False, in which case they are coerced to Python `float` objects.

  Note

  The `Numeric` type is designed to receive data from a database type that is explicitly known to be a decimal type (e.g. `DECIMAL`, `NUMERIC`, others) and not a floating point type (e.g. `FLOAT`, `REAL`, others). If the database column on the server is in fact a floating-point type type, such as `FLOAT` or `REAL`, use the `Float` type or a subclass, otherwise numeric coercion between `float`/`Decimal` may or may not function as expected.

  Note

  The Python `decimal.Decimal` class is generally slow performing; cPython 3.3 has now switched to use the cdecimal library natively. For older Python versions, the `cdecimal` library can be patched into any application where it will replace the `decimal` library fully, however this needs to be applied globally and before any other modules have been imported, as follows:

      import sys
      import cdecimal
      sys.modules["decimal"] = cdecimal

  Note that the `cdecimal` and `decimal` libraries are not compatible with each other, so patching `cdecimal` at the global level is the only way it can be used effectively with various DBAPIs that hardcode to import the `decimal` library.

  `__init__`(precision=None, scale=None, decimal_return_scale=None, asdecimal=True)

    Construct a Numeric.

    Parameters:

    - precision – the numeric precision for use in DDL `CREATE TABLE`.
    - scale – the numeric scale for use in DDL `CREATE TABLE`.
    - asdecimal – default True. Return whether or not values should be sent as Python Decimal objects, or as floats. Different DBAPIs send one or the other based on datatypes - the Numeric type will ensure that return values are one or the other across DBAPIs consistently.
    - decimal_return_scale –

      Default scale to use when converting from floats to Python decimals. Floating point values will typically be much longer due to decimal inaccuracy, and most floating point database types don’t have a notion of “scale”, so by default the float type looks for the first ten decimal places when converting. Specfiying this value will override that length. Types which do include an explicit ”.scale” value, such as the base `Numeric` as well as the MySQL float types, will use the value of ”.scale” as the default for decimal_return_scale, if not otherwise specified.

      New in version 0.9.0.

    When using the `Numeric` type, care should be taken to ensure that the asdecimal setting is apppropriate for the DBAPI in use - when Numeric applies a conversion from Decimal->float or float-> Decimal, this conversion incurs an additional performance overhead for all result columns received.

    DBAPIs that return Decimal natively (e.g. psycopg2) will have better accuracy and higher performance with a setting of `True`, as the native translation to Decimal reduces the amount of floating- point issues at play, and the Numeric type itself doesn’t need to apply any further conversions. However, another DBAPI which returns floats natively will incur an additional conversion overhead, and is still subject to floating point data loss - in which case `asdecimal=False` will at least remove the extra conversion overhead.

class `sqlalchemy.types.``PickleType`(protocol=2, pickler=None, comparator=None)

  Bases: `sqlalchemy.types.TypeDecorator`

  Holds Python objects, which are serialized using pickle.

  PickleType builds upon the Binary type to apply Python’s `pickle.dumps()` to incoming objects, and `pickle.loads()` on the way out, allowing any pickleable Python object to be stored as a serialized binary field.

  To allow ORM change events to propagate for elements associated with `PickleType`, see Mutation Tracking.

  `__init__`(protocol=2, pickler=None, comparator=None)

    Construct a PickleType.

    Parameters:

    - protocol – defaults to `pickle.HIGHEST_PROTOCOL`.
    - pickler – defaults to cPickle.pickle or pickle.pickle if cPickle is not available. May be any object with pickle-compatible `dumps` and ``loads` methods.
    - comparator – a 2-arg callable predicate used to compare values of this type. If left as `None`, the Python “equals” operator is used to compare values.

  `impl`

    alias of `LargeBinary`

class `sqlalchemy.types.``SchemaType`(name=None, schema=None, metadata=None, inherit_schema=False, quote=None, _create_events=True)

  Bases: `sqlalchemy.sql.expression.SchemaEventTarget`

  Mark a type as possibly requiring schema-level DDL for usage.

  Supports types that must be explicitly created/dropped (i.e. PG ENUM type) as well as types that are complimented by table or schema level constraints, triggers, and other rules.

  `SchemaType` classes can also be targets for the `DDLEvents.before_parent_attach()` and `DDLEvents.after_parent_attach()` events, where the events fire off surrounding the association of the type object with a parent `Column`.

  See also

  `Enum`

  `Boolean`

  `adapt`(impltype, **kw)
  `bind`
  `copy`(**kw)
  `create`(bind=None, checkfirst=False)

    Issue CREATE ddl for this type, if applicable.

  `drop`(bind=None, checkfirst=False)

    Issue DROP ddl for this type, if applicable.

class `sqlalchemy.types.``SmallInteger`

  Bases: `sqlalchemy.types.Integer`

  A type for smaller `int` integers.

  Typically generates a `SMALLINT` in DDL, and otherwise acts like a normal `Integer` on the Python side.

class `sqlalchemy.types.``String`(length=None, collation=None, convert_unicode=False, unicode_error=None, _warn_on_bytestring=False)

  Bases: `sqlalchemy.types.Concatenable`, `sqlalchemy.types.TypeEngine`

  The base for all string and character types.

  In SQL, corresponds to VARCHAR. Can also take Python unicode objects and encode to the database’s encoding in bind params (and the reverse for result sets.)

  The length field is usually required when the String type is used within a CREATE TABLE statement, as VARCHAR requires a length on most databases.

  `__init__`(length=None, collation=None, convert_unicode=False, unicode_error=None, _warn_on_bytestring=False)

    Create a string-holding type.

    Parameters:

    - length – optional, a length for the column for use in DDL and CAST expressions. 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 if a `VARCHAR` with no length is included. Whether the value is interpreted as bytes or characters is database specific.
    - collation –

      Optional, a column-level collation for use in DDL and CAST expressions. Renders using the COLLATE keyword supported by SQLite, MySQL, and Postgresql. E.g.:

          >>> from sqlalchemy import cast, select, String
          >>> print select([cast('some string', String(collation='utf8'))])
          SELECT CAST(:param_1 AS VARCHAR COLLATE utf8) AS anon_1

      New in version 0.8: Added support for COLLATE to all string types.

    - convert_unicode –

      When set to `True`, the `String` type will assume that input is to be passed as Python `unicode` objects, and results returned as Python `unicode` objects. If the DBAPI in use does not support Python unicode (which is fewer and fewer these days), SQLAlchemy will encode/decode the value, using the value of the `encoding` parameter passed to `create_engine()` as the encoding.

      When using a DBAPI that natively supports Python unicode objects, this flag generally does not need to be set. For columns that are explicitly intended to store non-ASCII data, the `Unicode` or `UnicodeText` types should be used regardless, which feature the same behavior of `convert_unicode` but also indicate an underlying column type that directly supports unicode, such as `NVARCHAR`.

      For the extremely rare case that Python `unicode` is to be encoded/decoded by SQLAlchemy on a backend that does natively support Python `unicode`, the value `force` can be passed here which will cause SQLAlchemy’s encode/decode services to be used unconditionally.

    - unicode_error – Optional, a method to use to handle Unicode conversion errors. Behaves like the `errors` keyword argument to the standard library’s `string.decode()` functions. This flag requires that `convert_unicode` is set to `force` - otherwise, SQLAlchemy is not guaranteed to handle the task of unicode conversion. Note that this flag adds significant performance overhead to row-fetching operations for backends that already return unicode objects natively (which most DBAPIs do). This flag should only be used as a last resort for reading strings from a column with varied or corrupted encodings.

class `sqlalchemy.types.``Text`(length=None, collation=None, convert_unicode=False, unicode_error=None, _warn_on_bytestring=False)

  Bases: `sqlalchemy.types.String`

  A variably sized string type.

  In SQL, usually corresponds to CLOB or TEXT. Can also take Python unicode objects and encode to the database’s encoding in bind params (and the reverse for result sets.) In general, TEXT objects do not have a length; while some databases will accept a length argument here, it will be rejected by others.

class `sqlalchemy.types.``Time`(timezone=False)

  Bases: `sqlalchemy.types._DateAffinity`, `sqlalchemy.types.TypeEngine`

  A type for `datetime.time()` objects.

class `sqlalchemy.types.``Unicode`(length=None, **kwargs)

  Bases: `sqlalchemy.types.String`

  A variable length Unicode string type.

  The `Unicode` type is a `String` subclass that assumes input and output as Python `unicode` data, and in that regard is equivalent to the usage of the `convert_unicode` flag with the `String` type. However, unlike plain `String`, it also implies an underlying column type that is explicitly supporting of non-ASCII data, such as `NVARCHAR` on Oracle and SQL Server. This can impact the output of `CREATE TABLE` statements and `CAST` functions at the dialect level, and can also affect the handling of bound parameters in some specific DBAPI scenarios.

  The encoding used by the `Unicode` type is usually determined by the DBAPI itself; most modern DBAPIs feature support for Python `unicode` objects as bound values and result set values, and the encoding should be configured as detailed in the notes for the target DBAPI in the Dialects section.

  For those DBAPIs which do not support, or are not configured to accommodate Python `unicode` objects directly, SQLAlchemy does the encoding and decoding outside of the DBAPI. The encoding in this scenario is determined by the `encoding` flag passed to `create_engine()`.

  When using the `Unicode` type, it is only appropriate to pass Python `unicode` objects, and not plain `str`. If a plain `str` is passed under Python 2, a warning is emitted. If you notice your application emitting these warnings but you’re not sure of the source of them, the Python `warnings` filter, documented at http://docs.python.org/library/warnings.html, can be used to turn these warnings into exceptions which will illustrate a stack trace:

      import warnings
      warnings.simplefilter('error')

  For an application that wishes to pass plain bytestrings and Python `unicode` objects to the `Unicode` type equally, the bytestrings must first be decoded into unicode. The recipe at Coercing Encoded Strings to Unicode illustrates how this is done.

  See also:

  > `UnicodeText` - unlengthed textual counterpart to `Unicode`.

  `__init__`(length=None, **kwargs)

    Create a `Unicode` object.

    Parameters are the same as that of `String`, with the exception that `convert_unicode` defaults to `True`.

class `sqlalchemy.types.``UnicodeText`(length=None, **kwargs)

  Bases: `sqlalchemy.types.Text`

  An unbounded-length Unicode string type.

  See `Unicode` for details on the unicode behavior of this object.

  Like `Unicode`, usage the `UnicodeText` type implies a unicode-capable type being used on the backend, such as `NCLOB`, `NTEXT`.

  `__init__`(length=None, **kwargs)

    Create a Unicode-converting Text type.

    Parameters are the same as that of `Text`, with the exception that `convert_unicode` defaults to `True`.

## SQL Standard Types

The SQL standard types always create database column types of the same name when `CREATE TABLE` is issued. Some types may not be supported on all databases.

class `sqlalchemy.types.``BIGINT`

  Bases: `sqlalchemy.types.BigInteger`

  The SQL BIGINT type.

class `sqlalchemy.types.``BINARY`(length=None)

  Bases: `sqlalchemy.types._Binary`

  The SQL BINARY type.

class `sqlalchemy.types.``BLOB`(length=None)

  Bases: `sqlalchemy.types.LargeBinary`

  The SQL BLOB type.

class `sqlalchemy.types.``BOOLEAN`(create_constraint=True, name=None, _create_events=True)

  Bases: `sqlalchemy.types.Boolean`

  The SQL BOOLEAN type.

class `sqlalchemy.types.``CHAR`(length=None, collation=None, convert_unicode=False, unicode_error=None, _warn_on_bytestring=False)

  Bases: `sqlalchemy.types.String`

  The SQL CHAR type.

class `sqlalchemy.types.``CLOB`(length=None, collation=None, convert_unicode=False, unicode_error=None, _warn_on_bytestring=False)

  Bases: `sqlalchemy.types.Text`

  The CLOB type.

  This type is found in Oracle and Informix.

class `sqlalchemy.types.``DATE`

  Bases: `sqlalchemy.types.Date`

  The SQL DATE type.

class `sqlalchemy.types.``DATETIME`(timezone=False)

  Bases: `sqlalchemy.types.DateTime`

  The SQL DATETIME type.

class `sqlalchemy.types.``DECIMAL`(precision=None, scale=None, decimal_return_scale=None, asdecimal=True)

  Bases: `sqlalchemy.types.Numeric`

  The SQL DECIMAL type.

class `sqlalchemy.types.``FLOAT`(precision=None, asdecimal=False, decimal_return_scale=None, **kwargs)

  Bases: `sqlalchemy.types.Float`

  The SQL FLOAT type.

`sqlalchemy.types.``INT`

  alias of `INTEGER`

class `sqlalchemy.types.``INTEGER`

  Bases: `sqlalchemy.types.Integer`

  The SQL INT or INTEGER type.

class `sqlalchemy.types.``NCHAR`(length=None, **kwargs)

  Bases: `sqlalchemy.types.Unicode`

  The SQL NCHAR type.

class `sqlalchemy.types.``NVARCHAR`(length=None, **kwargs)

  Bases: `sqlalchemy.types.Unicode`

  The SQL NVARCHAR type.

class `sqlalchemy.types.``NUMERIC`(precision=None, scale=None, decimal_return_scale=None, asdecimal=True)

  Bases: `sqlalchemy.types.Numeric`

  The SQL NUMERIC type.

class `sqlalchemy.types.``REAL`(precision=None, asdecimal=False, decimal_return_scale=None, **kwargs)

  Bases: `sqlalchemy.types.Float`

  The SQL REAL type.

class `sqlalchemy.types.``SMALLINT`

  Bases: `sqlalchemy.types.SmallInteger`

  The SQL SMALLINT type.

class `sqlalchemy.types.``TEXT`(length=None, collation=None, convert_unicode=False, unicode_error=None, _warn_on_bytestring=False)

  Bases: `sqlalchemy.types.Text`

  The SQL TEXT type.

class `sqlalchemy.types.``TIME`(timezone=False)

  Bases: `sqlalchemy.types.Time`

  The SQL TIME type.

class `sqlalchemy.types.``TIMESTAMP`(timezone=False)

  Bases: `sqlalchemy.types.DateTime`

  The SQL TIMESTAMP type.

class `sqlalchemy.types.``VARBINARY`(length=None)

  Bases: `sqlalchemy.types._Binary`

  The SQL VARBINARY type.

class `sqlalchemy.types.``VARCHAR`(length=None, collation=None, convert_unicode=False, unicode_error=None, _warn_on_bytestring=False)

  Bases: `sqlalchemy.types.String`

  The SQL VARCHAR type.

## Vendor-Specific Types

Database-specific types are also available for import from each database’s dialect module. See the Dialects reference for the database you’re interested in.

For example, MySQL has a `BIGINT` type and PostgreSQL has an `INET` type. To use these, import them from the module explicitly:

    from sqlalchemy.dialects import mysql

    table = Table('foo', metadata,
        Column('id', mysql.BIGINT),
        Column('enumerates', mysql.ENUM('a', 'b', 'c'))
    )

Or some PostgreSQL types:

    from sqlalchemy.dialects import postgresql

    table = Table('foo', metadata,
        Column('ipaddress', postgresql.INET),
        Column('elements', postgresql.ARRAY(String))
    )

Each dialect provides the full set of typenames supported by that backend within its __all__ collection, so that a simple import * or similar will import all supported types as implemented for that backend:

    from sqlalchemy.dialects.postgresql import *

    t = Table('mytable', metadata,
               Column('id', INTEGER, primary_key=True),
               Column('name', VARCHAR(300)),
               Column('inetaddr', INET)
    )

Where above, the INTEGER and VARCHAR types are ultimately from sqlalchemy.types, and INET is specific to the Postgresql dialect.

Some dialect level types have the same name as the SQL standard type, but also provide additional arguments. For example, MySQL implements the full range of character and string types including additional arguments such as collation and charset:

    from sqlalchemy.dialects.mysql import VARCHAR, TEXT

    table = Table('foo', meta,
        Column('col1', VARCHAR(200, collation='binary')),
        Column('col2', TEXT(charset='latin1'))
    )