### Navigation

- index
- modules |
- Camelot documentation »
- Module code »

# Source code for sqlalchemy.types

    # sqlalchemy/types.py
    # Copyright (C) 2005-2011 the SQLAlchemy authors and contributors <see AUTHORS file>
    #
    # This module is part of SQLAlchemy and is released under
    # the MIT License: http://www.opensource.org/licenses/mit-license.php

    """defines genericized SQL types, each represented by a subclass of
    :class:`~sqlalchemy.types.AbstractType`.  Dialects define further subclasses of these
    types.

    For more information see the SQLAlchemy documentation on types.

    """
    __all__ = [ 'TypeEngine', 'TypeDecorator', 'AbstractType', 'UserDefinedType',
                'INT', 'CHAR', 'VARCHAR', 'NCHAR', 'NVARCHAR','TEXT', 'Text',
                'FLOAT', 'NUMERIC', 'DECIMAL', 'TIMESTAMP', 'DATETIME', 'CLOB',
                'BLOB', 'BOOLEAN', 'SMALLINT', 'INTEGER', 'DATE', 'TIME',
                'String', 'Integer', 'SmallInteger', 'BigInteger', 'Numeric',
                'Float', 'DateTime', 'Date', 'Time', 'LargeBinary', 'Binary',
                'Boolean', 'Unicode', 'MutableType', 'Concatenable',
                'UnicodeText','PickleType', 'Interval', 'type_map', 'Enum' ]

    import inspect
    import datetime as dt
    from decimal import Decimal as _python_Decimal
    import codecs

    from sqlalchemy import exc, schema
    from sqlalchemy.sql import expression, operators
    import sys
    schema.types = expression.sqltypes =sys.modules['sqlalchemy.types']
    from sqlalchemy.util import pickle
    from sqlalchemy.sql.visitors import Visitable
    from sqlalchemy import util
    from sqlalchemy import processors
    import collections
    default = util.importlater("sqlalchemy.engine", "default")

    NoneType = type(None)
    if util.jython:
        import array

    class AbstractType(Visitable):

        def copy_value(self, value):
            return value

        def bind_processor(self, dialect):
            """Defines a bind parameter processing function.

            :param dialect: Dialect instance in use.

            """

            return None

        def result_processor(self, dialect, coltype):
            """Defines a result-column processing function.

            :param dialect: Dialect instance in use.

            :param coltype: DBAPI coltype argument received in cursor.description.

            """

            return None

        def compare_values(self, x, y):
            """Compare two values for equality."""

            return x == y

        def is_mutable(self):
            """Return True if the target Python type is 'mutable'.

            This allows systems like the ORM to know if a column value can
            be considered 'not changed' by comparing the identity of
            objects alone.  Values such as dicts, lists which
            are serialized into strings are examples of "mutable"
            column structures.

            When this method is overridden, :meth:`copy_value` should
            also be supplied.   The :class:`.MutableType` mixin
            is recommended as a helper.

            """
            return False

        def get_dbapi_type(self, dbapi):
            """Return the corresponding type object from the underlying DB-API, if
            any.

             This can be useful for calling ``setinputsizes()``, for example.

            """
            return None

        def _adapt_expression(self, op, othertype):
            """evaluate the return type of <self> <op> <othertype>,
            and apply any adaptations to the given operator.

            """
            return op, self

        @util.memoized_property
        def _type_affinity(self):
            """Return a rudimental 'affinity' value expressing the general class
            of type."""

            typ = None
            for t in self.__class__.__mro__:
                if t is TypeEngine or t is UserDefinedType:
                    return typ
                elif issubclass(t, TypeEngine):
                    typ = t
            else:
                return self.__class__

        def _coerce_compared_value(self, op, value):
            """Suggest a type for a 'coerced' Python value in an expression.

            Given an operator and value, gives the type a chance
            to return a type which the value should be coerced into.

            The default behavior here is conservative; if the right-hand
            side is already coerced into a SQL type based on its
            Python type, it is usually left alone.

            End-user functionality extension here should generally be via
            :class:`.TypeDecorator`, which provides more liberal behavior in that
            it defaults to coercing the other side of the expression into this
            type, thus applying special Python conversions above and beyond those
            needed by the DBAPI to both ides. It also provides the public method
            :meth:`.TypeDecorator.coerce_compared_value` which is intended for
            end-user customization of this behavior.

            """

            _coerced_type = type_map.get(type(value), NULLTYPE)
            if _coerced_type is NULLTYPE or _coerced_type._type_affinity \
                is self._type_affinity:
                return self
            else:
                return _coerced_type

        def _compare_type_affinity(self, other):
            return self._type_affinity is other._type_affinity

        def compile(self, dialect=None):
            """Produce a string-compiled form of this :class:`.TypeEngine`.

            When called with no arguments, uses a "default" dialect
            to produce a string result.

            :param dialect: a :class:`.Dialect` instance.

            """
            # arg, return value is inconsistent with
            # ClauseElement.compile()....this is a mistake.

            if not dialect:
                dialect = self._default_dialect

            return dialect.type_compiler.process(self)

        @property
        def _default_dialect(self):
            if self.__class__.__module__.startswith("sqlalchemy.dialects"):
                tokens = self.__class__.__module__.split(".")[0:3]
                mod = ".".join(tokens)
                return getattr(__import__(mod).dialects, tokens[-1]).dialect()
            else:
                return default.DefaultDialect()

        def __str__(self):
            # Py3K
            #return unicode(self.compile())
            # Py2K
            return unicode(self.compile()).\
                            encode('ascii', 'backslashreplace')
            # end Py2K

        def __init__(self, *args, **kwargs):
            # supports getargspec of the __init__ method
            # used by generic __repr__
            pass

        def __repr__(self):
            return "%s(%s)" % (
                self.__class__.__name__,
                ", ".join("%s=%r" % (k, getattr(self, k, None))
                          for k in inspect.getargspec(self.__init__)[0][1:]))

    class TypeEngine(AbstractType):
        """Base for built-in types."""

        @util.memoized_property
        def _impl_dict(self):
            return {}

        def dialect_impl(self, dialect, **kwargs):
            """Return a dialect-specific implementation for this :class:`.TypeEngine`."""

            key = dialect.__class__, dialect.server_version_info
            try:
                return self._impl_dict[key]
            except KeyError:
                return self._impl_dict.setdefault(key,
                        dialect.type_descriptor(self))

        def __getstate__(self):
            d = self.__dict__.copy()
            d.pop('_impl_dict', None)
            return d

        def bind_processor(self, dialect):
            """Return a conversion function for processing bind values.

            Returns a callable which will receive a bind parameter value
            as the sole positional argument and will return a value to
            send to the DB-API.

            If processing is not necessary, the method should return ``None``.

            """
            return None

        def result_processor(self, dialect, coltype):
            """Return a conversion function for processing result row values.

            Returns a callable which will receive a result row column
            value as the sole positional argument and will return a value
            to return to the user.

            If processing is not necessary, the method should return ``None``.

            """
            return None

        def adapt(self, cls):
            return cls()

    class UserDefinedType(TypeEngine):
        """Base for user defined types.

        This should be the base of new types.  Note that
        for most cases, :class:`TypeDecorator` is probably
        more appropriate::

          import sqlalchemy.types as types

          class MyType(types.UserDefinedType):
              def __init__(self, precision = 8):
                  self.precision = precision

              def get_col_spec(self):
                  return "MYTYPE(%s)" % self.precision

              def bind_processor(self, dialect):
                  def process(value):
                      return value
                  return process

              def result_processor(self, dialect, coltype):
                  def process(value):
                      return value
                  return process

        Once the type is made, it's immediately usable::

          table = Table('foo', meta,
              Column('id', Integer, primary_key=True),
              Column('data', MyType(16))
              )

        """
        __visit_name__ = "user_defined"

        def _adapt_expression(self, op, othertype):
            """evaluate the return type of <self> <op> <othertype>,
            and apply any adaptations to the given operator.

            """
            return self.adapt_operator(op), self

        def adapt_operator(self, op):
            """A hook which allows the given operator to be adapted
            to something new.

            See also UserDefinedType._adapt_expression(), an as-yet-
            semi-public method with greater capability in this regard.

            """
            return op

    class TypeDecorator(AbstractType):
        """Allows the creation of types which add additional functionality
        to an existing type.

        This method is preferred to direct subclassing of SQLAlchemy's
        built-in types as it ensures that all required functionality of
        the underlying type is kept in place.

        Typical usage::

          import sqlalchemy.types as types

          class MyType(types.TypeDecorator):
              '''Prefixes Unicode values with "PREFIX:" on the way in and
              strips it off on the way out.
              '''

              impl = types.Unicode

              def process_bind_param(self, value, dialect):
                  return "PREFIX:" + value

              def process_result_value(self, value, dialect):
                  return value[7:]

              def copy(self):
                  return MyType(self.impl.length)

        The class-level "impl" variable is required, and can reference any
        TypeEngine class.  Alternatively, the load_dialect_impl() method
        can be used to provide different type classes based on the dialect
        given; in this case, the "impl" variable can reference
        ``TypeEngine`` as a placeholder.

        Types that receive a Python type that isn't similar to the ultimate type
        used may want to define the :meth:`TypeDecorator.coerce_compared_value`
        method. This is used to give the expression system a hint when coercing
        Python objects into bind parameters within expressions. Consider this
        expression::

            mytable.c.somecol + datetime.date(2009, 5, 15)

        Above, if "somecol" is an ``Integer`` variant, it makes sense that
        we're doing date arithmetic, where above is usually interpreted
        by databases as adding a number of days to the given date.
        The expression system does the right thing by not attempting to
        coerce the "date()" value into an integer-oriented bind parameter.

        However, in the case of ``TypeDecorator``, we are usually changing an
        incoming Python type to something new - ``TypeDecorator`` by default will
        "coerce" the non-typed side to be the same type as itself. Such as below,
        we define an "epoch" type that stores a date value as an integer::

            class MyEpochType(types.TypeDecorator):
                impl = types.Integer

                epoch = datetime.date(1970, 1, 1)

                def process_bind_param(self, value, dialect):
                    return (value - self.epoch).days

                def process_result_value(self, value, dialect):
                    return self.epoch + timedelta(days=value)

        Our expression of ``somecol + date`` with the above type will coerce the
        "date" on the right side to also be treated as ``MyEpochType``.

        This behavior can be overridden via the
        :meth:`~TypeDecorator.coerce_compared_value` method, which returns a type
        that should be used for the value of the expression. Below we set it such
        that an integer value will be treated as an ``Integer``, and any other
        value is assumed to be a date and will be treated as a ``MyEpochType``::

            def coerce_compared_value(self, op, value):
                if isinstance(value, int):
                    return Integer()
                else:
                    return self

        """

        __visit_name__ = "type_decorator"

        def __init__(self, *args, **kwargs):
            """Construct a :class:`.TypeDecorator`.

            Arguments sent here are passed to the constructor
            of the class assigned to the ``impl`` class level attribute,
            where the ``self.impl`` attribute is assigned an instance
            of the implementation type.  If ``impl`` at the class level
            is already an instance, then it's assigned to ``self.impl``
            as is.

            Subclasses can override this to customize the generation
            of ``self.impl``.

            """
            if not hasattr(self.__class__, 'impl'):
                raise AssertionError("TypeDecorator implementations "
                                     "require a class-level variable "
                                     "'impl' which refers to the class of "
                                     "type being decorated")
            self.impl = to_instance(self.__class__.impl, *args, **kwargs)

        def adapt(self, cls):
            """Produce an "adapted" form of this type, given an "impl" class
            to work with.

            This method is used internally to associate generic
            types with "implementation" types that are specific to a particular
            dialect.
            """
            return cls()

        def dialect_impl(self, dialect):
            """Return a dialect-specific implementation for this :class:`.TypeEngine`.

            See also :meth:`type_engine`, :meth:`load_dialect_impl`.
            :meth:`load_dialect_impl` is an end-user overrideable
            hook.

            """

            key = (dialect.__class__, dialect.server_version_info)

            try:
                return self._impl_dict[key]
            except KeyError:
                pass

            adapted = dialect.type_descriptor(self)
            if adapted is not self:
                self._impl_dict[key] = adapted
                return adapted

            # otherwise adapt the impl type, link
            # to a copy of this TypeDecorator and return
            # that.
            typedesc = self.load_dialect_impl(dialect).dialect_impl(dialect)
            tt = self.copy()
            if not isinstance(tt, self.__class__):
                raise AssertionError('Type object %s does not properly '
                                     'implement the copy() method, it must '
                                     'return an object of type %s' % (self,
                                     self.__class__))
            tt.impl = typedesc
            self._impl_dict[key] = tt
            return tt

        @util.memoized_property
        def _impl_dict(self):
            return {}

        @util.memoized_property
        def _type_affinity(self):
            return self.impl._type_affinity

        def type_engine(self, dialect):
            """Return a dialect-specific :class:`.TypeEngine` instance
            for this :class:`.TypeDecorator`.

            In most cases this returns a dialect-adapted form of
            the :class:`.TypeEngine` type represented by ``self.impl``.
            Makes usage of :meth:`dialect_impl` but also traverses
            into wrapped :class:`.TypeDecorator` instances.
            Behavior can be customized here by overriding :meth:`load_dialect_impl`.

            """
            adapted = dialect.type_descriptor(self)
            if adapted is not self:
                return adapted
            elif isinstance(self.impl, TypeDecorator):
                return self.impl.type_engine(dialect)
            else:
                return self.load_dialect_impl(dialect)

        def load_dialect_impl(self, dialect):
            """Return a :class:`.TypeEngine` object corresponding to a dialect.

            This is an end-user override hook that can be used to provide
            differing types depending on the given dialect.  It is used
            by the :class:`.TypeDecorator` implementation of :meth:`type_engine`
            and :meth:`dialect_impl` to help determine what type should ultimately be returned
            for a given :class:`.TypeDecorator`.

            By default returns ``self.impl``.

            """
            return self.impl

        def __getattr__(self, key):
            """Proxy all other undefined accessors to the underlying
            implementation."""

            return getattr(self.impl, key)

        def process_bind_param(self, value, dialect):
            """Receive a bound parameter value to be converted.

            Subclasses override this method to return the
            value that should be passed along to the underlying
            :class:`.TypeEngine` object, and from there to the
            DBAPI ``execute()`` method.

            :param value: the value.  Can be None.
            :param dialect: the :class:`.Dialect` in use.

            """
            raise NotImplementedError()

        def process_result_value(self, value, dialect):
            """Receive a result-row column value to be converted.

            Subclasses override this method to return the
            value that should be passed back to the application,
            given a value that is already processed by
            the underlying :class:`.TypeEngine` object, originally
            from the DBAPI cursor method ``fetchone()`` or similar.

            :param value: the value.  Can be None.
            :param dialect: the :class:`.Dialect` in use.

            """
            raise NotImplementedError()

        def bind_processor(self, dialect):
            """Provide a bound value processing function for the given :class:`.Dialect`.

            This is the method that fulfills the :class:`.TypeEngine`
            contract for bound value conversion.   :class:`.TypeDecorator`
            will wrap a user-defined implementation of
            :meth:`process_bind_param` here.

            User-defined code can override this method directly,
            though its likely best to use :meth:`process_bind_param` so that
            the processing provided by ``self.impl`` is maintained.

            """
            if self.__class__.process_bind_param.func_code \
                is not TypeDecorator.process_bind_param.func_code:
                process_param = self.process_bind_param
                impl_processor = self.impl.bind_processor(dialect)
                if impl_processor:
                    def process(value):
                        return impl_processor(process_param(value, dialect))

                else:
                    def process(value):
                        return process_param(value, dialect)

                return process
            else:
                return self.impl.bind_processor(dialect)

        def result_processor(self, dialect, coltype):
            """Provide a result value processing function for the given :class:`.Dialect`.

            This is the method that fulfills the :class:`.TypeEngine`
            contract for result value conversion.   :class:`.TypeDecorator`
            will wrap a user-defined implementation of
            :meth:`process_result_value` here.

            User-defined code can override this method directly,
            though its likely best to use :meth:`process_result_value` so that
            the processing provided by ``self.impl`` is maintained.

            """
            if self.__class__.process_result_value.func_code \
                is not TypeDecorator.process_result_value.func_code:
                process_value = self.process_result_value
                impl_processor = self.impl.result_processor(dialect,
                        coltype)
                if impl_processor:
                    def process(value):
                        return process_value(impl_processor(value), dialect)

                else:
                    def process(value):
                        return process_value(value, dialect)

                return process
            else:
                return self.impl.result_processor(dialect, coltype)

        def coerce_compared_value(self, op, value):
            """Suggest a type for a 'coerced' Python value in an expression.

            By default, returns self.   This method is called by
            the expression system when an object using this type is
            on the left or right side of an expression against a plain Python
            object which does not yet have a SQLAlchemy type assigned::

                expr = table.c.somecolumn + 35

            Where above, if ``somecolumn`` uses this type, this method will
            be called with the value ``operator.add``
            and ``35``.  The return value is whatever SQLAlchemy type should
            be used for ``35`` for this particular operation.

            """
            return self

        def _coerce_compared_value(self, op, value):
            """See :meth:`.AbstractType._coerce_compared_value` for a description."""

            return self.coerce_compared_value(op, value)

        def copy(self):
            """Produce a copy of this :class:`.TypeDecorator` instance.

            This is a shallow copy and is provided to fulfill part of
            the :class:`.TypeEngine` contract.  It usually does not
            need to be overridden unless the user-defined :class:`.TypeDecorator`
            has local state that should be deep-copied.

            """
            instance = self.__class__.__new__(self.__class__)
            instance.__dict__.update(self.__dict__)
            instance._impl_dict = {}
            return instance

        def get_dbapi_type(self, dbapi):
            """Return the DBAPI type object represented by this :class:`.TypeDecorator`.

            By default this calls upon :meth:`.TypeEngine.get_dbapi_type` of the
            underlying "impl".
            """
            return self.impl.get_dbapi_type(dbapi)

        def copy_value(self, value):
            """Given a value, produce a copy of it.

            By default this calls upon :meth:`.TypeEngine.copy_value`
            of the underlying "impl".

            :meth:`.copy_value` will return the object
            itself, assuming "mutability" is not enabled.
            Only the :class:`.MutableType` mixin provides a copy
            function that actually produces a new object.
            The copying function is used by the ORM when
            "mutable" types are used, to memoize the original
            version of an object as loaded from the database,
            which is then compared to the possibly mutated
            version to check for changes.

            """
            return self.impl.copy_value(value)

        def compare_values(self, x, y):
            """Given two values, compare them for equality.

            By default this calls upon :meth:`.TypeEngine.compare_values`
            of the underlying "impl", which in turn usually
            uses the Python equals operator ``==``.

            This function is used by the ORM to compare
            an original-loaded value with an intercepted
            "changed" value, to determine if a net change
            has occurred.

            """
            return self.impl.compare_values(x, y)

        def is_mutable(self):
            """Return True if the target Python type is 'mutable'.

            This allows systems like the ORM to know if a column value can
            be considered 'not changed' by comparing the identity of
            objects alone.  Values such as dicts, lists which
            are serialized into strings are examples of "mutable"
            column structures.

            When this method is overridden, :meth:`copy_value` should
            also be supplied.   The :class:`.MutableType` mixin
            is recommended as a helper.

            """
            return self.impl.is_mutable()

        def _adapt_expression(self, op, othertype):
            op, typ =self.impl._adapt_expression(op, othertype)
            if typ is self.impl:
                return op, self
            else:
                return op, typ

    class MutableType(object):
        """A mixin that marks a :class:`TypeEngine` as representing
        a mutable Python object type.

        "mutable" means that changes can occur in place to a value
        of this type.   Examples includes Python lists, dictionaries,
        and sets, as well as user-defined objects.  The primary
        need for identification of "mutable" types is by the ORM,
        which applies special rules to such values in order to guarantee
        that changes are detected.  These rules may have a significant
        performance impact, described below.

        A :class:`MutableType` usually allows a flag called
        ``mutable=True`` to enable/disable the "mutability" flag,
        represented on this class by :meth:`is_mutable`.  Examples
        include :class:`PickleType` and
        :class:`~sqlalchemy.dialects.postgresql.base.ARRAY`.  Setting
        this flag to ``False`` effectively disables any mutability-
        specific behavior by the ORM.

        :meth:`copy_value` and :meth:`compare_values` represent a copy
        and compare function for values of this type - implementing
        subclasses should override these appropriately.

        The usage of mutable types has significant performance
        implications when using the ORM. In order to detect changes, the
        ORM must create a copy of the value when it is first
        accessed, so that changes to the current value can be compared
        against the "clean" database-loaded value. Additionally, when the
        ORM checks to see if any data requires flushing, it must scan
        through all instances in the session which are known to have
        "mutable" attributes and compare the current value of each
        one to its "clean"
        value. So for example, if the Session contains 6000 objects (a
        fairly large amount) and autoflush is enabled, every individual
        execution of :class:`Query` will require a full scan of that subset of
        the 6000 objects that have mutable attributes, possibly resulting
        in tens of thousands of additional method calls for every query.

        Note that for small numbers (< 100 in the Session at a time)
        of objects with "mutable" values, the performance degradation is
        negligible.  In most cases it's likely that the convenience allowed
        by "mutable" change detection outweighs the performance penalty.

        It is perfectly fine to represent "mutable" data types with the
        "mutable" flag set to False, which eliminates any performance
        issues. It means that the ORM will only reliably detect changes
        for values of this type if a newly modified value is of a different
        identity (i.e., ``id(value)``) than what was present before -
        i.e., instead of operations like these::

            myobject.somedict['foo'] = 'bar'
            myobject.someset.add('bar')
            myobject.somelist.append('bar')

        You'd instead say::

            myobject.somevalue = {'foo':'bar'}
            myobject.someset = myobject.someset.union(['bar'])
            myobject.somelist = myobject.somelist + ['bar']

        A future release of SQLAlchemy will include instrumented
        collection support for mutable types, such that at least usage of
        plain Python datastructures will be able to emit events for
        in-place changes, removing the need for pessimistic scanning for
        changes.

        """

        def is_mutable(self):
            """Return True if the target Python type is 'mutable'.

            For :class:`.MutableType`, this method is set to
            return ``True``.

            """
            return True

        def copy_value(self, value):
            """Unimplemented."""
            raise NotImplementedError()

        def compare_values(self, x, y):
            """Compare *x* == *y*."""
            return x == y

    def to_instance(typeobj, *arg, **kw):
        if typeobj is None:
            return NULLTYPE

        if util.callable(typeobj):
            return typeobj(*arg, **kw)
        else:
            return typeobj

    def adapt_type(typeobj, colspecs):
        if isinstance(typeobj, type):
            typeobj = typeobj()
        for t in typeobj.__class__.__mro__[0:-1]:
            try:
                impltype = colspecs[t]
                break
            except KeyError:
                pass
        else:
            # couldnt adapt - so just return the type itself
            # (it may be a user-defined type)
            return typeobj
        # if we adapted the given generic type to a database-specific type,
        # but it turns out the originally given "generic" type
        # is actually a subclass of our resulting type, then we were already
        # given a more specific type than that required; so use that.
        if (issubclass(typeobj.__class__, impltype)):
            return typeobj
        return typeobj.adapt(impltype)

    class NullType(TypeEngine):
        """An unknown type.

        NullTypes will stand in if :class:`~sqlalchemy.Table` reflection
        encounters a column data type unknown to SQLAlchemy.  The
        resulting columns are nearly fully usable: the DB-API adapter will
        handle all translation to and from the database data type.

        NullType does not have sufficient information to particpate in a
        ``CREATE TABLE`` statement and will raise an exception if
        encountered during a :meth:`~sqlalchemy.Table.create` operation.

        """
        __visit_name__ = 'null'

        def _adapt_expression(self, op, othertype):
            if isinstance(othertype, NullType) or not operators.is_commutative(op):
                return op, self
            else:
                return othertype._adapt_expression(op, self)

    NullTypeEngine = NullType

    class Concatenable(object):
        """A mixin that marks a type as supporting 'concatenation',
        typically strings."""

        def _adapt_expression(self, op, othertype):
            if op is operators.add and issubclass(othertype._type_affinity,
                    (Concatenable, NullType)):
                return operators.concat_op, self
            else:
                return op, self

    class _DateAffinity(object):
        """Mixin date/time specific expression adaptations.

        Rules are implemented within Date,Time,Interval,DateTime, Numeric,
        Integer. Based on http://www.postgresql.org/docs/current/static
        /functions-datetime.html.

        """

        @property
        def _expression_adaptations(self):
            raise NotImplementedError()

        _blank_dict = util.frozendict()
        def _adapt_expression(self, op, othertype):
            othertype = othertype._type_affinity
            return op, \
                    self._expression_adaptations.get(op, self._blank_dict).\
                    get(othertype, NULLTYPE)

    class String(Concatenable, 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.

        """

        __visit_name__ = 'string'

        def __init__(self, length=None, convert_unicode=False,
                            assert_unicode=None, unicode_error=None,
                            _warn_on_bytestring=False
                            ):
            """
            Create a string-holding type.

            :param length: optional, a length for the column for use in
              DDL statements.  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.  Whether the value is
              interpreted as bytes or characters is database specific.

            :param convert_unicode: defaults to False.  If True, the
              type will do what is necessary in order to accept
              Python Unicode objects as bind parameters, and to return
              Python Unicode objects in result rows.   This may
              require SQLAlchemy to explicitly coerce incoming Python
              unicodes into an encoding, and from an encoding
              back to Unicode, or it may not require any interaction
              from SQLAlchemy at all, depending on the DBAPI in use.

              When SQLAlchemy performs the encoding/decoding,
              the encoding used is configured via
              :attr:`~sqlalchemy.engine.base.Dialect.encoding`, which
              defaults to `utf-8`.

              The "convert_unicode" behavior can also be turned on
              for all String types by setting
              :attr:`sqlalchemy.engine.base.Dialect.convert_unicode`
              on create_engine().

              To instruct SQLAlchemy to perform Unicode encoding/decoding
              even on a platform that already handles Unicode natively,
              set convert_unicode='force'.  This will incur significant
              performance overhead when fetching unicode result columns.

            :param assert_unicode: Deprecated.  A warning is raised in all cases
              when a non-Unicode object is passed when SQLAlchemy would coerce
              into an encoding (note: but **not** when the DBAPI handles unicode
              objects natively). To suppress or raise this warning to an error,
              use the Python warnings filter documented at:
              http://docs.python.org/library/warnings.html

            :param 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 an absolute last resort for reading
              strings from a column with varied or corrupted encodings,
              which only applies to databases that accept invalid encodings
              in the first place (i.e. MySQL.  *not* PG, Sqlite, etc.)

            """
            if unicode_error is not None and convert_unicode != 'force':
                raise exc.ArgumentError("convert_unicode must be 'force' "
                                            "when unicode_error is set.")

            if assert_unicode:
                util.warn_deprecated('assert_unicode is deprecated. '
                                     'SQLAlchemy emits a warning in all '
                                     'cases where it would otherwise like '
                                     'to encode a Python unicode object '
                                     'into a specific encoding but a plain '
                                     'bytestring is received. This does '
                                     '*not* apply to DBAPIs that coerce '
                                     'Unicode natively.')
            self.length = length
            self.convert_unicode = convert_unicode
            self.unicode_error = unicode_error
            self._warn_on_bytestring = _warn_on_bytestring

        def adapt(self, impltype):
            return impltype(
                        length=self.length,
                        convert_unicode=self.convert_unicode,
                        unicode_error=self.unicode_error,
                        _warn_on_bytestring=True,
                        )

        def bind_processor(self, dialect):
            if self.convert_unicode or dialect.convert_unicode:
                if dialect.supports_unicode_binds and \
                    self.convert_unicode != 'force':
                    if self._warn_on_bytestring:
                        def process(value):
                            # Py3K
                            #if isinstance(value, bytes):
                            # Py2K
                            if isinstance(value, str):
                            # end Py2K
                                util.warn("Unicode type received non-unicode bind "
                                          "param value.")
                            return value
                        return process
                    else:
                        return None
                else:
                    encoder = codecs.getencoder(dialect.encoding)
                    warn_on_bytestring = self._warn_on_bytestring
                    def process(value):
                        if isinstance(value, unicode):
                            return encoder(value, self.unicode_error)[0]
                        elif warn_on_bytestring and value is not None:
                            util.warn("Unicode type received non-unicode bind "
                                      "param value")
                        return value
                return process
            else:
                return None

        def result_processor(self, dialect, coltype):
            wants_unicode = self.convert_unicode or dialect.convert_unicode
            needs_convert = wants_unicode and \
                            (dialect.returns_unicode_strings is not True or
                            self.convert_unicode == 'force')

            if needs_convert:
                to_unicode = processors.to_unicode_processor_factory(
                                        dialect.encoding, self.unicode_error)

                if dialect.returns_unicode_strings:
                    # we wouldn't be here unless convert_unicode='force'
                    # was specified, or the driver has erratic unicode-returning
                    # habits.  since we will be getting back unicode
                    # in most cases, we check for it (decode will fail).
                    def process(value):
                        if isinstance(value, unicode):
                            return value
                        else:
                            return to_unicode(value)
                    return process
                else:
                    # here, we assume that the object is not unicode,
                    # avoiding expensive isinstance() check.
                    return to_unicode
            else:
                return None

        def get_dbapi_type(self, dbapi):
            return dbapi.STRING

    class Text(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.)

        """
        __visit_name__ = 'text'

    class Unicode(String):
        """A variable length Unicode string.

        The ``Unicode`` type is a :class:`String` which converts Python
        ``unicode`` objects (i.e., strings that are defined as
        ``u'somevalue'``) into encoded bytestrings when passing the value
        to the database driver, and similarly decodes values from the
        database back into Python ``unicode`` objects.

        It's roughly equivalent to using a ``String`` object with
        ``convert_unicode=True``, however
        the type has other significances in that it implies the usage
        of a unicode-capable type being used on the backend, such as NVARCHAR.
        This may affect what type is emitted when issuing CREATE TABLE
        and also may effect some DBAPI-specific details, such as type
        information passed along to ``setinputsizes()``.

        When using the ``Unicode`` type, it is only appropriate to pass
        Python ``unicode`` objects, and not plain ``str``.  If a
        bytestring (``str``) is passed, a runtime warning is issued.  If
        you notice your application raising these warnings but you're not
        sure where, the Python ``warnings`` filter can be used to turn
        these warnings into exceptions which will illustrate a stack
        trace::

          import warnings
          warnings.simplefilter('error')

        Bytestrings sent to and received from the database are encoded
        using the dialect's
        :attr:`~sqlalchemy.engine.base.Dialect.encoding`, which defaults
        to `utf-8`.

        """

        __visit_name__ = 'unicode'

        def __init__(self, length=None, **kwargs):
            """
            Create a Unicode-converting String type.

            :param length: optional, a length for the column for use in
              DDL statements.  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.  Whether the value is
              interpreted as bytes or characters is database specific.

            :param \**kwargs: passed through to the underlying ``String``
              type.

            """
            kwargs.setdefault('convert_unicode', True)
            kwargs.setdefault('_warn_on_bytestring', True)
            super(Unicode, self).__init__(length=length, **kwargs)

    class UnicodeText(Text):
        """An unbounded-length Unicode string.

        See :class:`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.

        """

        __visit_name__ = 'unicode_text'

        def __init__(self, length=None, **kwargs):
            """
            Create a Unicode-converting Text type.

            :param length: optional, a length for the column for use in
              DDL statements.  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.  Whether the value is
              interpreted as bytes or characters is database specific.

            """
            kwargs.setdefault('convert_unicode', True)
            kwargs.setdefault('_warn_on_bytestring', True)
            super(UnicodeText, self).__init__(length=length, **kwargs)

    class Integer(_DateAffinity, TypeEngine):
        """A type for ``int`` integers."""

        __visit_name__ = 'integer'

        def get_dbapi_type(self, dbapi):
            return dbapi.NUMBER

        @util.memoized_property
        def _expression_adaptations(self):
            # TODO: need a dictionary object that will
            # handle operators generically here, this is incomplete
            return {
                operators.add:{
                    Date:Date,
                    Integer:Integer,
                    Numeric:Numeric,
                },
                operators.mul:{
                    Interval:Interval,
                    Integer:Integer,
                    Numeric:Numeric,
                },
                # Py2K
                operators.div:{
                    Integer:Integer,
                    Numeric:Numeric,
                },
                # end Py2K
                operators.truediv:{
                    Integer:Integer,
                    Numeric:Numeric,
                },
                operators.sub:{
                    Integer:Integer,
                    Numeric:Numeric,
                },
            }

    class SmallInteger(Integer):
        """A type for smaller ``int`` integers.

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

        """

        __visit_name__ = 'small_integer'

    class BigInteger(Integer):
        """A type for bigger ``int`` integers.

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

        """

        __visit_name__ = 'big_integer'

    class Numeric(_DateAffinity, TypeEngine):
        """A type for fixed precision numbers.

        Typically generates DECIMAL or NUMERIC.  Returns
        ``decimal.Decimal`` objects by default, applying
        conversion as needed.

        """

        __visit_name__ = 'numeric'

        def __init__(self, precision=None, scale=None, asdecimal=True):
            """
            Construct a Numeric.

            :param precision: the numeric precision for use in DDL ``CREATE
              TABLE``.

            :param scale: the numeric scale for use in DDL ``CREATE TABLE``.

            :param 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.

            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.

            """
            self.precision = precision
            self.scale = scale
            self.asdecimal = asdecimal

        def adapt(self, impltype):
            return impltype(
                    precision=self.precision,
                    scale=self.scale,
                    asdecimal=self.asdecimal)

        def get_dbapi_type(self, dbapi):
            return dbapi.NUMBER

        def bind_processor(self, dialect):
            if dialect.supports_native_decimal:
                return None
            else:
                return processors.to_float

        def result_processor(self, dialect, coltype):
            if self.asdecimal:
                if dialect.supports_native_decimal:
                    # we're a "numeric", DBAPI will give us Decimal directly
                    return None
                else:
                    util.warn('Dialect %s+%s does *not* support Decimal '
                              'objects natively, and SQLAlchemy must '
                              'convert from floating point - rounding '
                              'errors and other issues may occur. Please '
                              'consider storing Decimal numbers as strings '
                              'or integers on this platform for lossless '
                              'storage.' % (dialect.name, dialect.driver))

                    # we're a "numeric", DBAPI returns floats, convert.
                    if self.scale is not None:
                        return processors.to_decimal_processor_factory(
                                    _python_Decimal, self.scale)
                    else:
                        return processors.to_decimal_processor_factory(
                                    _python_Decimal)
            else:
                if dialect.supports_native_decimal:
                    return processors.to_float
                else:
                    return None

        @util.memoized_property
        def _expression_adaptations(self):
            return {
                operators.mul:{
                    Interval:Interval,
                    Numeric:Numeric,
                    Integer:Numeric,
                },
                # Py2K
                operators.div:{
                    Numeric:Numeric,
                    Integer:Numeric,
                },
                # end Py2K
                operators.truediv:{
                    Numeric:Numeric,
                    Integer:Numeric,
                },
                operators.add:{
                    Numeric:Numeric,
                    Integer:Numeric,
                },
                operators.sub:{
                    Numeric:Numeric,
                    Integer:Numeric,
                }
            }

    class Float(Numeric):
        """A type for ``float`` numbers.

        Returns Python ``float`` objects by default, applying
        conversion as needed.

        """

        __visit_name__ = 'float'

        def __init__(self, precision=None, asdecimal=False, **kwargs):
            """
            Construct a Float.

            :param precision: the numeric precision for use in DDL ``CREATE
               TABLE``.

            :param asdecimal: the same flag as that of :class:`Numeric`, but
              defaults to ``False``.   Note that setting this flag to ``True``
              results in floating point conversion.

            """
            self.precision = precision
            self.asdecimal = asdecimal

        def adapt(self, impltype):
            return impltype(precision=self.precision, asdecimal=self.asdecimal)

        def result_processor(self, dialect, coltype):
            if self.asdecimal:
                return processors.to_decimal_processor_factory(_python_Decimal)
            else:
                return None

        @util.memoized_property
        def _expression_adaptations(self):
            return {
                operators.mul:{
                    Interval:Interval,
                    Numeric:Float,
                },
                # Py2K
                operators.div:{
                    Numeric:Float,
                },
                # end Py2K
                operators.truediv:{
                    Numeric:Float,
                },
                operators.add:{
                    Numeric:Float,
                },
                operators.sub:{
                    Numeric:Float,
                }
            }

    class DateTime(_DateAffinity, 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.

        """

        __visit_name__ = 'datetime'

        def __init__(self, timezone=False):
            self.timezone = timezone

        def adapt(self, impltype):
            return impltype(timezone=self.timezone)

        def get_dbapi_type(self, dbapi):
            return dbapi.DATETIME

        @util.memoized_property
        def _expression_adaptations(self):
            return {
                operators.add:{
                    Interval:DateTime,
                },
                operators.sub:{
                    Interval:DateTime,
                    DateTime:Interval,
                },
            }

    class Date(_DateAffinity,TypeEngine):
        """A type for ``datetime.date()`` objects."""

        __visit_name__ = 'date'

        def get_dbapi_type(self, dbapi):
            return dbapi.DATETIME

        @util.memoized_property
        def _expression_adaptations(self):
            return {
                operators.add:{
                    Integer:Date,
                    Interval:DateTime,
                    Time:DateTime,
                },
                operators.sub:{
                    # date - integer = date
                    Integer:Date,

                    # date - date = integer.
                    Date:Integer,

                    Interval:DateTime,

                    # date - datetime = interval,
                    # this one is not in the PG docs
                    # but works
                    DateTime:Interval,
                },
            }

    class Time(_DateAffinity,TypeEngine):
        """A type for ``datetime.time()`` objects."""

        __visit_name__ = 'time'

        def __init__(self, timezone=False):
            self.timezone = timezone

        def adapt(self, impltype):
            return impltype(timezone=self.timezone)

        def get_dbapi_type(self, dbapi):
            return dbapi.DATETIME

        @util.memoized_property
        def _expression_adaptations(self):
            return {
                operators.add:{
                    Date:DateTime,
                    Interval:Time
                },
                operators.sub:{
                    Time:Interval,
                    Interval:Time,
                },
            }

    class _Binary(TypeEngine):
        """Define base behavior for binary types."""

        def __init__(self, length=None):
            self.length = length

        # Python 3 - sqlite3 doesn't need the `Binary` conversion
        # here, though pg8000 does to indicate "bytea"
        def bind_processor(self, dialect):
            DBAPIBinary = dialect.dbapi.Binary
            def process(value):
                if value is not None:
                    return DBAPIBinary(value)
                else:
                    return None
            return process

        # Python 3 has native bytes() type
        # both sqlite3 and pg8000 seem to return it
        # (i.e. and not 'memoryview')
        # Py2K
        def result_processor(self, dialect, coltype):
            if util.jython:
                def process(value):
                    if value is not None:
                        if isinstance(value, array.array):
                            return value.tostring()
                        return str(value)
                    else:
                        return None
            else:
                process = processors.to_str
            return process
        # end Py2K

        def _coerce_compared_value(self, op, value):
            """See :meth:`.AbstractType._coerce_compared_value` for a description."""

            if isinstance(value, basestring):
                return self
            else:
                return super(_Binary, self)._coerce_compared_value(op, value)

        def adapt(self, impltype):
            return impltype(length=self.length)

        def get_dbapi_type(self, dbapi):
            return dbapi.BINARY

    class LargeBinary(_Binary):
        """A type for large binary byte data.

        The Binary type generates BLOB or BYTEA when tables are created,
        and also converts incoming values using the ``Binary`` callable
        provided by each DB-API.

        """

        __visit_name__ = 'large_binary'

        def __init__(self, length=None):
            """
            Construct a LargeBinary type.

            :param 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.

            """
            _Binary.__init__(self, length=length)

    class Binary(LargeBinary):
        """Deprecated.  Renamed to LargeBinary."""

        def __init__(self, *arg, **kw):
            util.warn_deprecated('The Binary type has been renamed to '
                                 'LargeBinary.')
            LargeBinary.__init__(self, *arg, **kw)

    class SchemaType(object):
        """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.

        """

        def __init__(self, **kw):
            self.name = kw.pop('name', None)
            self.quote = kw.pop('quote', None)
            self.schema = kw.pop('schema', None)
            self.metadata = kw.pop('metadata', None)
            if self.metadata:
                self.metadata.append_ddl_listener('before-create',
                        util.portable_instancemethod(self._on_metadata_create))
                self.metadata.append_ddl_listener('after-drop',
                        util.portable_instancemethod(self._on_metadata_drop))

        def _set_parent(self, column):
            column._on_table_attach(util.portable_instancemethod(self._set_table))

        def _set_table(self, table, column):
            table.append_ddl_listener('before-create',
                                      util.portable_instancemethod(
                                            self._on_table_create))
            table.append_ddl_listener('after-drop',
                                      util.portable_instancemethod(
                                            self._on_table_drop))
            if self.metadata is None:
                table.metadata.append_ddl_listener('before-create',
                        util.portable_instancemethod(self._on_metadata_create))
                table.metadata.append_ddl_listener('after-drop',
                        util.portable_instancemethod(self._on_metadata_drop))

        @property
        def bind(self):
            return self.metadata and self.metadata.bind or None

        def create(self, bind=None, checkfirst=False):
            """Issue CREATE ddl for this type, if applicable."""

            if bind is None:
                bind = schema._bind_or_error(self)
            t = self.dialect_impl(bind.dialect)
            if t is not self and isinstance(t, SchemaType):
                t.create(bind=bind, checkfirst=checkfirst)

        def drop(self, bind=None, checkfirst=False):
            """Issue DROP ddl for this type, if applicable."""

            if bind is None:
                bind = schema._bind_or_error(self)
            t = self.dialect_impl(bind.dialect)
            if t is not self and isinstance(t, SchemaType):
                t.drop(bind=bind, checkfirst=checkfirst)

        def _on_table_create(self, event, target, bind, **kw):
            t = self.dialect_impl(bind.dialect)
            if t is not self and isinstance(t, SchemaType):
                t._on_table_create(event, target, bind, **kw)

        def _on_table_drop(self, event, target, bind, **kw):
            t = self.dialect_impl(bind.dialect)
            if t is not self and isinstance(t, SchemaType):
                t._on_table_drop(event, target, bind, **kw)

        def _on_metadata_create(self, event, target, bind, **kw):
            t = self.dialect_impl(bind.dialect)
            if t is not self and isinstance(t, SchemaType):
                t._on_metadata_create(event, target, bind, **kw)

        def _on_metadata_drop(self, event, target, bind, **kw):
            t = self.dialect_impl(bind.dialect)
            if t is not self and isinstance(t, SchemaType):
                t._on_metadata_drop(event, target, bind, **kw)

    class Enum(String, 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.
        """

        __visit_name__ = 'enum'

        def __init__(self, *enums, **kw):
            """Construct an enum.

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

            :param \*enums: string or unicode enumeration labels. If unicode
               labels are present, the `convert_unicode` flag is auto-enabled.

            :param 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.

            :param 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 it's existence. The type is
               only dropped when ``drop_all()`` is called for that ``Table``
               object's metadata, however.

            :param 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.

            :param native_enum: Use the database's native ENUM type when
               available. Defaults to True. When False, uses VARCHAR + check
               constraint for all backends.

            :param schema: Schemaname 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.

            :param quote: Force quoting to be on or off on the type's name. If
               left as the default of `None`, the usual schema-level "case
               sensitive"/"reserved name" rules are used to determine if this
               type's name should be quoted.

            """
            self.enums = enums
            self.native_enum = kw.pop('native_enum', True)
            convert_unicode= kw.pop('convert_unicode', None)
            if convert_unicode is None:
                for e in enums:
                    if isinstance(e, unicode):
                        convert_unicode = True
                        break
                else:
                    convert_unicode = False

            if self.enums:
                length =max(len(x) for x in self.enums)
            else:
                length = 0
            String.__init__(self,
                            length =length,
                            convert_unicode=convert_unicode,
                            )
            SchemaType.__init__(self, **kw)

        def _should_create_constraint(self, compiler):
            return not self.native_enum or \
                        not compiler.dialect.supports_native_enum

        def _set_table(self, table, column):
            if self.native_enum:
                SchemaType._set_table(self, table, column)

            e = schema.CheckConstraint(
                            column.in_(self.enums),
                            name=self.name,
                            _create_rule=util.portable_instancemethod(
                                            self._should_create_constraint)
                        )
            table.append_constraint(e)

        def adapt(self, impltype):
            if issubclass(impltype, Enum):
                return impltype(name=self.name,
                            quote=self.quote,
                            schema=self.schema,
                            metadata=self.metadata,
                            convert_unicode=self.convert_unicode,
                            native_enum=self.native_enum,
                            *self.enums
                            )
            else:
                return super(Enum, self).adapt(impltype)

    class PickleType(MutableType, 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.

        **Note:** be sure to read the notes for :class:`MutableType` regarding
        ORM performance implications.

        """

        impl = LargeBinary

        def __init__(self, protocol=pickle.HIGHEST_PROTOCOL,
                        pickler=None, mutable=True, comparator=None):
            """
            Construct a PickleType.

            :param protocol: defaults to ``pickle.HIGHEST_PROTOCOL``.

            :param pickler: defaults to cPickle.pickle or pickle.pickle if
              cPickle is not available.  May be any object with
              pickle-compatible ``dumps` and ``loads`` methods.

            :param mutable: defaults to True; implements
              :meth:`AbstractType.is_mutable`.   When ``True``, incoming
              objects should provide an ``__eq__()`` method which
              performs the desired deep comparison of members, or the
              ``comparator`` argument must be present.

            :param comparator: optional. a 2-arg callable predicate used
              to compare values of this type.  Otherwise,
              the == operator is used to compare values.

            """
            self.protocol = protocol
            self.pickler = pickler or pickle
            self.mutable = mutable
            self.comparator = comparator
            super(PickleType, self).__init__()

        def bind_processor(self, dialect):
            impl_processor = self.impl.bind_processor(dialect)
            dumps = self.pickler.dumps
            protocol = self.protocol
            if impl_processor:
                def process(value):
                    if value is not None:
                        value = dumps(value, protocol)
                    return impl_processor(value)
            else:
                def process(value):
                    if value is not None:
                        value = dumps(value, protocol)
                    return value
            return process

        def result_processor(self, dialect, coltype):
            impl_processor = self.impl.result_processor(dialect, coltype)
            loads = self.pickler.loads
            if impl_processor:
                def process(value):
                    value = impl_processor(value)
                    if value is None:
                        return None
                    return loads(value)
            else:
                def process(value):
                    if value is None:
                        return None
                    return loads(value)
            return process

        def copy_value(self, value):
            if self.mutable:
                return self.pickler.loads(
                            self.pickler.dumps(value, self.protocol))
            else:
                return value

        def compare_values(self, x, y):
            if self.comparator:
                return self.comparator(x, y)
            else:
                return x == y

        def is_mutable(self):
            """Return True if the target Python type is 'mutable'.

            When this method is overridden, :meth:`copy_value` should
            also be supplied.   The :class:`.MutableType` mixin
            is recommended as a helper.

            """
            return self.mutable

    class Boolean(TypeEngine, SchemaType):
        """A bool datatype.

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

        """

        __visit_name__ = 'boolean'

        def __init__(self, create_constraint=True, name=None):
            """Construct a Boolean.

            :param 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.

            :param name: if a CHECK constraint is generated, specify
              the name of the constraint.

            """
            self.create_constraint = create_constraint
            self.name = name

        def _should_create_constraint(self, compiler):
            return not compiler.dialect.supports_native_boolean

        def _set_table(self, table, column):
            if not self.create_constraint:
                return

            e = schema.CheckConstraint(
                            column.in_([0, 1]),
                            name=self.name,
                            _create_rule=util.portable_instancemethod(
                                        self._should_create_constraint)
                        )
            table.append_constraint(e)

        def bind_processor(self, dialect):
            if dialect.supports_native_boolean:
                return None
            else:
                return processors.boolean_to_int

        def result_processor(self, dialect, coltype):
            if dialect.supports_native_boolean:
                return None
            else:
                return processors.int_to_boolean

    class Interval(_DateAffinity, 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
        :attr:`~sqlalchemy.sql.expression.func`).

        """

        impl = DateTime
        epoch = dt.datetime.utcfromtimestamp(0)

        def __init__(self, native=True,
                            second_precision=None,
                            day_precision=None):
            """Construct an Interval object.

            :param 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.

            :param second_precision: For native interval types
              which support a "fractional seconds precision" parameter,
              i.e. Oracle and Postgresql

            :param day_precision: for native interval types which
              support a "day precision" parameter, i.e. Oracle.

            """
            super(Interval, self).__init__()
            self.native = native
            self.second_precision = second_precision
            self.day_precision = day_precision

        def adapt(self, cls):
            if self.native:
                return cls._adapt_from_generic_interval(self)
            else:
                return self

        def bind_processor(self, dialect):
            impl_processor = self.impl.bind_processor(dialect)
            epoch = self.epoch
            if impl_processor:
                def process(value):
                    if value is not None:
                        value = epoch + value
                    return impl_processor(value)
            else:
                def process(value):
                    if value is not None:
                        value = epoch + value
                    return value
            return process

        def result_processor(self, dialect, coltype):
            impl_processor = self.impl.result_processor(dialect, coltype)
            epoch = self.epoch
            if impl_processor:
                def process(value):
                    value = impl_processor(value)
                    if value is None:
                        return None
                    return value - epoch
            else:
                def process(value):
                    if value is None:
                        return None
                    return value - epoch
            return process

        @util.memoized_property
        def _expression_adaptations(self):
            return {
                operators.add:{
                    Date:DateTime,
                    Interval:Interval,
                    DateTime:DateTime,
                    Time:Time,
                },
                operators.sub:{
                    Interval:Interval
                },
                operators.mul:{
                    Numeric:Interval
                },
                operators.truediv: {
                    Numeric:Interval
                },
                # Py2K
                operators.div: {
                    Numeric:Interval
                }
                # end Py2K
            }

        @property
        def _type_affinity(self):
            return Interval

        def _coerce_compared_value(self, op, value):
            """See :meth:`.AbstractType._coerce_compared_value` for a description."""

            return self.impl._coerce_compared_value(op, value)

    class FLOAT(Float):
        """The SQL FLOAT type."""

        __visit_name__ = 'FLOAT'

    class NUMERIC(Numeric):
        """The SQL NUMERIC type."""

        __visit_name__ = 'NUMERIC'

    class DECIMAL(Numeric):
        """The SQL DECIMAL type."""

        __visit_name__ = 'DECIMAL'

    class INTEGER(Integer):
        """The SQL INT or INTEGER type."""

        __visit_name__ = 'INTEGER'
    INT = INTEGER

    class SMALLINT(SmallInteger):
        """The SQL SMALLINT type."""

        __visit_name__ = 'SMALLINT'

    class BIGINT(BigInteger):
        """The SQL BIGINT type."""

        __visit_name__ = 'BIGINT'

    class TIMESTAMP(DateTime):
        """The SQL TIMESTAMP type."""

        __visit_name__ = 'TIMESTAMP'

        def get_dbapi_type(self, dbapi):
            return dbapi.TIMESTAMP

    class DATETIME(DateTime):
        """The SQL DATETIME type."""

        __visit_name__ = 'DATETIME'

    class DATE(Date):
        """The SQL DATE type."""

        __visit_name__ = 'DATE'

    class TIME(Time):
        """The SQL TIME type."""

        __visit_name__ = 'TIME'

    class TEXT(Text):
        """The SQL TEXT type."""

        __visit_name__ = 'TEXT'

    class CLOB(Text):
        """The CLOB type.

        This type is found in Oracle and Informix.
        """

        __visit_name__ = 'CLOB'

    class VARCHAR(String):
        """The SQL VARCHAR type."""

        __visit_name__ = 'VARCHAR'

    class NVARCHAR(Unicode):
        """The SQL NVARCHAR type."""

        __visit_name__ = 'NVARCHAR'

    class CHAR(String):
        """The SQL CHAR type."""

        __visit_name__ = 'CHAR'

    class NCHAR(Unicode):
        """The SQL NCHAR type."""

        __visit_name__ = 'NCHAR'

    class BLOB(LargeBinary):
        """The SQL BLOB type."""

        __visit_name__ = 'BLOB'

    class BINARY(_Binary):
        """The SQL BINARY type."""

        __visit_name__ = 'BINARY'

    class VARBINARY(_Binary):
        """The SQL VARBINARY type."""

        __visit_name__ = 'VARBINARY'

    class BOOLEAN(Boolean):
        """The SQL BOOLEAN type."""

        __visit_name__ = 'BOOLEAN'

    NULLTYPE = NullType()
    BOOLEANTYPE = Boolean()
    STRINGTYPE = String()

    # using VARCHAR/NCHAR so that we dont get the genericized "String"
    # type which usually resolves to TEXT/CLOB
    # NOTE: this dict is not meant to be public and will be underscored
    # in 0.7, see [ticket:1870].

    type_map = {
        str: String(),
        # Py3K
        #bytes : LargeBinary(),
        # Py2K
        unicode : Unicode(),
        # end Py2K
        int : Integer(),
        float : Numeric(),
        bool: BOOLEANTYPE,
        _python_Decimal : Numeric(),
        dt.date : Date(),
        dt.datetime : DateTime(),
        dt.time : Time(),
        dt.timedelta : Interval(),
        NoneType: NULLTYPE
    }

### Navigation

- index
- modules |
- Camelot documentation »
- Module code »

Comments
blog comments powered by Disqus