text: # sqlalchemy/types.py
  # Copyright (C) 2005-2013 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', 'REAL', 'DECIMAL', 'TIMESTAMP', 'DATETIME',
              'CLOB', 'BLOB', 'BINARY', 'VARBINARY', 'BOOLEAN', 'BIGINT',
              'SMALLINT', 'INTEGER', 'DATE', 'TIME', 'String', 'Integer',
              'SmallInteger', 'BigInteger', 'Numeric', 'Float', 'DateTime',
              'Date', 'Time', 'LargeBinary', 'Binary', 'Boolean', 'Unicode',
              'Concatenable', 'UnicodeText', 'PickleType', 'Interval', 'Enum']
  
  import datetime as dt
  import codecs
  
  from . import exc, schema, util, processors, events, event
  from .sql import operators
  from .sql.expression import _DefaultColumnComparator
  from .util import pickle
  from .sql.visitors import Visitable
  import decimal
  default = util.importlater("sqlalchemy.engine", "default")
  
  NoneType = type(None)
  if util.jython:
      import array
  
  
  class AbstractType(Visitable):
      """Base for all types - not needed except for backwards
      compatibility."""
  
  
  class TypeEngine(AbstractType):
      """Base for built-in types."""
  
      class Comparator(_DefaultColumnComparator):
          """Base class for custom comparison operations defined at the
          type level.  See :attr:`.TypeEngine.comparator_factory`.
  
          The public base class for :class:`.TypeEngine.Comparator`
          is :class:`.ColumnOperators`.
  
          """
  
          def __init__(self, expr):
              self.expr = expr
  
          def __reduce__(self):
              return _reconstitute_comparator, (self.expr, )
  
      hashable = True
      """Flag, if False, means values from this type aren't hashable.
  
      Used by the ORM when uniquing result lists.
  
      """
  
      comparator_factory = Comparator
      """A :class:`.TypeEngine.Comparator` class which will apply
      to operations performed by owning :class:`.ColumnElement` objects.
  
      The :attr:`.comparator_factory` attribute is a hook consulted by
      the core expression system when column and SQL expression operations
      are performed.   When a :class:`.TypeEngine.Comparator` class is
      associated with this attribute, it allows custom re-definition of
      all existing operators, as well as definition of new operators.
      Existing operators include those provided by Python operator overloading
      such as :meth:`.operators.ColumnOperators.__add__` and
      :meth:`.operators.ColumnOperators.__eq__`,
      those provided as standard
      attributes of :class:`.operators.ColumnOperators` such as
      :meth:`.operators.ColumnOperators.like`
      and :meth:`.operators.ColumnOperators.in_`.
  
      Rudimentary usage of this hook is allowed through simple subclassing
      of existing types, or alternatively by using :class:`.TypeDecorator`.
      See the documentation section :ref:`types_operators` for examples.
  
      .. versionadded:: 0.8  The expression system was enhanced to support
        customization of operators on a per-type level.
  
      """
  
      def copy_value(self, value):
          return value
  
      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``.
  
          :param dialect: Dialect instance in use.
  
          """
          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``.
  
          :param dialect: Dialect instance in use.
  
          :param coltype: DBAPI coltype argument received in cursor.description.
  
          """
          return None
  
      def column_expression(self, colexpr):
          """Given a SELECT column expression, return a wrapping SQL expression.
  
          This is typically a SQL function that wraps a column expression
          as rendered in the columns clause of a SELECT statement.
          It is used for special data types that require
          columns to be wrapped in some special database function in order
          to coerce the value before being sent back to the application.
          It is the SQL analogue of the :meth:`.TypeEngine.result_processor`
          method.
  
          The method is evaluated at statement compile time, as opposed
          to statement construction time.
  
          See also:
  
          :ref:`types_sql_value_processing`
  
          """
  
          return None
  
      @util.memoized_property
      def _has_column_expression(self):
          """memoized boolean, check if column_expression is implemented.
  
          Allows the method to be skipped for the vast majority of expression
          types that don't use this feature.
  
          """
  
          return self.__class__.column_expression.__code__ \
              is not TypeEngine.column_expression.__code__
  
      def bind_expression(self, bindvalue):
          """"Given a bind value (i.e. a :class:`.BindParameter` instance),
          return a SQL expression in its place.
  
          This is typically a SQL function that wraps the existing bound
          parameter within the statement.  It is used for special data types
          that require literals being wrapped in some special database function
          in order to coerce an application-level value into a database-specific
          format.  It is the SQL analogue of the
          :meth:`.TypeEngine.bind_processor` method.
  
          The method is evaluated at statement compile time, as opposed
          to statement construction time.
  
          Note that this method, when implemented, should always return
          the exact same structure, without any conditional logic, as it
          may be used in an executemany() call against an arbitrary number
          of bound parameter sets.
  
          See also:
  
          :ref:`types_sql_value_processing`
  
          """
          return None
  
      @util.memoized_property
      def _has_bind_expression(self):
          """memoized boolean, check if bind_expression is implemented.
  
          Allows the method to be skipped for the vast majority of expression
          types that don't use this feature.
  
          """
  
          return self.__class__.bind_expression.__code__ \
              is not TypeEngine.bind_expression.__code__
  
      def compare_values(self, x, y):
          """Compare two values for equality."""
  
          return x == y
  
      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
  
      @property
      def python_type(self):
          """Return the Python type object expected to be returned
          by instances of this type, if known.
  
          Basically, for those types which enforce a return type,
          or are known across the board to do such for all common
          DBAPIs (like ``int`` for example), will return that type.
  
          If a return type is not defined, raises
          ``NotImplementedError``.
  
          Note that any type also accommodates NULL in SQL which
          means you can also get back ``None`` from any type
          in practice.
  
          """
          raise NotImplementedError()
  
      def with_variant(self, type_, dialect_name):
          """Produce a new type object that will utilize the given
          type when applied to the dialect of the given name.
  
          e.g.::
  
              from sqlalchemy.types import String
              from sqlalchemy.dialects import mysql
  
              s = String()
  
              s = s.with_variant(mysql.VARCHAR(collation='foo'), 'mysql')
  
          The construction of :meth:`.TypeEngine.with_variant` is always
          from the "fallback" type to that which is dialect specific.
          The returned type is an instance of :class:`.Variant`, which
          itself provides a :meth:`~sqlalchemy.types.Variant.with_variant`
          that can be called repeatedly.
  
          :param type_: a :class:`.TypeEngine` that will be selected
           as a variant from the originating type, when a dialect
           of the given name is in use.
          :param dialect_name: base name of the dialect which uses
           this type. (i.e. ``'postgresql'``, ``'mysql'``, etc.)
  
          .. versionadded:: 0.7.2
  
          """
          return Variant(self, {dialect_name: type_})
  
      @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 dialect_impl(self, dialect):
          """Return a dialect-specific implementation for this
          :class:`.TypeEngine`.
  
          """
          try:
              return dialect._type_memos[self]['impl']
          except KeyError:
              return self._dialect_info(dialect)['impl']
  
      def _cached_bind_processor(self, dialect):
          """Return a dialect-specific bind processor for this type."""
  
          try:
              return dialect._type_memos[self]['bind']
          except KeyError:
              d = self._dialect_info(dialect)
              d['bind'] = bp = d['impl'].bind_processor(dialect)
              return bp
  
      def _cached_result_processor(self, dialect, coltype):
          """Return a dialect-specific result processor for this type."""
  
          try:
              return dialect._type_memos[self][coltype]
          except KeyError:
              d = self._dialect_info(dialect)
              # key assumption: DBAPI type codes are
              # constants.  Else this dictionary would
              # grow unbounded.
              d[coltype] = rp = d['impl'].result_processor(dialect, coltype)
              return rp
  
      def _dialect_info(self, dialect):
          """Return a dialect-specific registry which
          caches a dialect-specific implementation, bind processing
          function, and one or more result processing functions."""
  
          if self in dialect._type_memos:
              return dialect._type_memos[self]
          else:
              impl = self._gen_dialect_impl(dialect)
              if impl is self:
                  impl = self.adapt(type(self))
              # this can't be self, else we create a cycle
              assert impl is not self
              dialect._type_memos[self] = d = {'impl': impl}
              return d
  
      def _gen_dialect_impl(self, dialect):
          return dialect.type_descriptor(self)
  
      def adapt(self, cls, **kw):
          """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 util.constructor_copy(self, cls, **kw)
  
      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):
  # start Py3K
          return str(self.compile())
  # end Py3K
  # start Py2K
  #        return unicode(self.compile()).\
  #                        encode('ascii', 'backslashreplace')
  # end Py2K
  
      def __init__(self, *args, **kwargs):
          """Support implementations that were passing arguments"""
          if args or kwargs:
              util.warn_deprecated("Passing arguments to type object "
                      "constructor %s is deprecated" % self.__class__)
  
      def __repr__(self):
          return util.generic_repr(self)
  
  
  def _reconstitute_comparator(expression):
      return expression.comparator
  
  
  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"
  
      class Comparator(TypeEngine.Comparator):
          def _adapt_expression(self, op, other_comparator):
              if hasattr(self.type, 'adapt_operator'):
                  util.warn_deprecated(
                      "UserDefinedType.adapt_operator is deprecated.  Create "
                       "a UserDefinedType.Comparator subclass instead which "
                       "generates the desired expression constructs, given a "
                       "particular operator."
                      )
                  return self.type.adapt_operator(op), self.type
              else:
                  return op, self.type
  
      comparator_factory = Comparator
  
      def coerce_compared_value(self, op, value):
          """Suggest a type for a 'coerced' Python value in an expression.
  
          Default behavior for :class:`.UserDefinedType` is the
          same as that of :class:`.TypeDecorator`; by default it returns
          ``self``, assuming the compared value should be coerced into
          the same type as this one.  See
          :meth:`.TypeDecorator.coerce_compared_value` for more detail.
  
          .. versionchanged:: 0.8 :meth:`.UserDefinedType.coerce_compared_value`
             now returns ``self`` by default, rather than falling onto the
             more fundamental behavior of
             :meth:`.TypeEngine.coerce_compared_value`.
  
          """
  
          return self
  
  
  class TypeDecorator(TypeEngine):
      """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" attribute 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,
          assuming the ``impl`` is a callable, and the resulting
          object is assigned to the ``self.impl`` instance attribute
          (thus overriding the class attribute of the same name).
  
          If the class level ``impl`` is not a callable (the unusual case),
          it will be assigned to the same instance attribute 'as-is',
          ignoring those arguments passed to the constructor.
  
          Subclasses can override this to customize the generation
          of ``self.impl`` entirely.
  
          """
  
          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)
  
      coerce_to_is_types = (util.NoneType, )
      """Specify those Python types which should be coerced at the expression
      level to "IS <constant>" when compared using ``==`` (and same for
          ``IS NOT`` in conjunction with ``!=``.
  
      For most SQLAlchemy types, this includes ``NoneType``, as well as ``bool``.
  
      :class:`.TypeDecorator` modifies this list to only include ``NoneType``,
      as typedecorator implementations that deal with boolean types are common.
  
      Custom :class:`.TypeDecorator` classes can override this attribute to
      return an empty tuple, in which case no values will be coerced to
      constants.
  
      ..versionadded:: 0.8.2
          Added :attr:`.TypeDecorator.coerce_to_is_types` to allow for easier
          control of ``__eq__()`` ``__ne__()`` operations.
  
      """
  
      class Comparator(TypeEngine.Comparator):
          def operate(self, op, *other, **kwargs):
              kwargs['_python_is_types'] = self.expr.type.coerce_to_is_types
              return super(TypeDecorator.Comparator, self).operate(
                                                          op, *other, **kwargs)
  
          def reverse_operate(self, op, other, **kwargs):
              kwargs['_python_is_types'] = self.expr.type.coerce_to_is_types
              return super(TypeDecorator.Comparator, self).reverse_operate(
                                                          op, other, **kwargs)
  
      @property
      def comparator_factory(self):
          return type("TDComparator",
                      (TypeDecorator.Comparator, self.impl.comparator_factory),
                      {})
  
      def _gen_dialect_impl(self, dialect):
          """
          #todo
          """
          adapted = dialect.type_descriptor(self)
          if adapted is not self:
              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
          return tt
  
      @property
      def _type_affinity(self):
          """
          #todo
          """
          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 type(adapted) is not type(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`
          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.
  
          The operation could be anything desired to perform custom
          behavior, such as transforming or serializing data.
          This could also be used as a hook for validating logic.
  
          This operation should be designed with the reverse operation
          in mind, which would be the process_result_value method of
          this class.
  
          :param value: Data to operate upon, of any type expected by
           this method in the subclass.  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 should implement this method to operate on data
          fetched from the database.
  
          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.
  
          The operation could be anything desired to perform custom
          behavior, such as transforming or serializing data.
          This could also be used as a hook for validating logic.
  
          :param value: Data to operate upon, of any type expected by
           this method in the subclass.  Can be ``None``.
          :param dialect: the :class:`.Dialect` in use.
  
          This operation should be designed to be reversible by
          the "process_bind_param" method of this class.
  
          """
  
          raise NotImplementedError()
  
      @util.memoized_property
      def _has_bind_processor(self):
          """memoized boolean, check if process_bind_param is implemented.
  
          Allows the base process_bind_param to raise
          NotImplementedError without needing to test an expensive
          exception throw.
  
          """
  
          return self.__class__.process_bind_param.__code__ \
              is not TypeDecorator.process_bind_param.__code__
  
      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.
  
          :param dialect: Dialect instance in use.
  
          This method is the reverse counterpart to the
          :meth:`result_processor` method of this class.
  
          """
          if self._has_bind_processor:
              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)
  
      @util.memoized_property
      def _has_result_processor(self):
          """memoized boolean, check if process_result_value is implemented.
  
          Allows the base process_result_value to raise
          NotImplementedError without needing to test an expensive
          exception throw.
  
          """
          return self.__class__.process_result_value.__code__ \
              is not TypeDecorator.process_result_value.__code__
  
      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.
  
          :param dialect: Dialect instance in use.
          :param coltype: An SQLAlchemy data type
  
          This method is the reverse counterpart to the
          :meth:`bind_processor` method of this class.
  
          """
          if self._has_result_processor:
              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 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__)
          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 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 __repr__(self):
          return util.generic_repr(self, to_inspect=self.impl)
  
  
  class Variant(TypeDecorator):
      """A wrapping type that selects among a variety of
      implementations based on dialect in use.
  
      The :class:`.Variant` type is typically constructed
      using the :meth:`.TypeEngine.with_variant` method.
  
      .. versionadded:: 0.7.2
  
      """
  
      def __init__(self, base, mapping):
          """Construct a new :class:`.Variant`.
  
          :param base: the base 'fallback' type
          :param mapping: dictionary of string dialect names to
            :class:`.TypeEngine` instances.
  
          """
          self.impl = base
          self.mapping = mapping
  
      def load_dialect_impl(self, dialect):
          if dialect.name in self.mapping:
              return self.mapping[dialect.name]
          else:
              return self.impl
  
      def with_variant(self, type_, dialect_name):
          """Return a new :class:`.Variant` which adds the given
          type + dialect name to the mapping, in addition to the
          mapping present in this :class:`.Variant`.
  
          :param type_: a :class:`.TypeEngine` that will be selected
           as a variant from the originating type, when a dialect
           of the given name is in use.
          :param dialect_name: base name of the dialect which uses
           this type. (i.e. ``'postgresql'``, ``'mysql'``, etc.)
  
          """
  
          if dialect_name in self.mapping:
              raise exc.ArgumentError(
                  "Dialect '%s' is already present in "
                  "the mapping for this Variant" % dialect_name)
          mapping = self.mapping.copy()
          mapping[dialect_name] = type_
          return Variant(self.impl, mapping)
  
  
  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'
  
      class Comparator(TypeEngine.Comparator):
          def _adapt_expression(self, op, other_comparator):
              if isinstance(other_comparator, NullType.Comparator) or \
                  not operators.is_commutative(op):
                  return op, self.expr.type
              else:
                  return other_comparator._adapt_expression(op, self)
      comparator_factory = Comparator
  
  NullTypeEngine = NullType
  
  
  class Concatenable(object):
      """A mixin that marks a type as supporting 'concatenation',
      typically strings."""
  
      class Comparator(TypeEngine.Comparator):
          def _adapt_expression(self, op, other_comparator):
              if op is operators.add and isinstance(other_comparator,
                      (Concatenable.Comparator, NullType.Comparator)):
                  return operators.concat_op, self.expr.type
              else:
                  return op, self.expr.type
  
      comparator_factory = Comparator
  
  
  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()
  
      class Comparator(TypeEngine.Comparator):
          _blank_dict = util.immutabledict()
  
          def _adapt_expression(self, op, other_comparator):
              othertype = other_comparator.type._type_affinity
              return op, \
                      self.type._expression_adaptations.get(op, self._blank_dict).\
                      get(othertype, NULLTYPE)
      comparator_factory = Comparator
  
  
  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, collation=None,
                          convert_unicode=False,
                          unicode_error=None,
                          _warn_on_bytestring=False
                          ):
          """
          Create a string-holding type.
  
          :param 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.
  
          :param 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
  
            .. versionadded:: 0.8 Added support for COLLATE to all
               string types.
  
          :param convert_unicode: When set to ``True``, the
            :class:`.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
            :func:`.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 :class:`.Unicode`
            or :class:`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.
  
          :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 a last resort for reading
            strings from a column with varied or corrupted encodings.
  
          """
          if unicode_error is not None and convert_unicode != 'force':
              raise exc.ArgumentError("convert_unicode must be 'force' "
                                          "when unicode_error is set.")
  
          self.length = length
          self.collation = collation
          self.convert_unicode = convert_unicode
          self.unicode_error = unicode_error
          self._warn_on_bytestring = _warn_on_bytestring
  
      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):
  # start Py3K
                          if isinstance(value, bytes):
  # end Py3K
  # start 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, str):
                          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, str):
                          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
  
      @property
      def python_type(self):
          if self.convert_unicode:
              return str
          else:
              return str
  
      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.)  In general, TEXT objects
      do not have a length; while some databases will accept a length
      argument here, it will be rejected by others.
  
      """
      __visit_name__ = 'text'
  
  
  class Unicode(String):
      """A variable length Unicode string type.
  
      The :class:`.Unicode` type is a :class:`.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 :class:`.String` type.
      However, unlike plain :class:`.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 :class:`.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 :ref:`dialect_toplevel` 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
      :func:`.create_engine`.
  
      When using the :class:`.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 :ref:`coerce_to_unicode` illustrates
      how this is done.
  
      See also:
  
          :class:`.UnicodeText` - unlengthed textual counterpart
          to :class:`.Unicode`.
  
      """
  
      __visit_name__ = 'unicode'
  
      def __init__(self, length=None, **kwargs):
          """
          Create a :class:`.Unicode` object.
  
          Parameters are the same as that of :class:`.String`,
          with the exception that ``convert_unicode``
          defaults to ``True``.
  
          """
          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 type.
  
      See :class:`.Unicode` for details on the unicode
      behavior of this object.
  
      Like :class:`.Unicode`, usage the :class:`.UnicodeText` type implies a
      unicode-capable type being used on the backend, such as
      ``NCLOB``, ``NTEXT``.
  
      """
  
      __visit_name__ = 'unicode_text'
  
      def __init__(self, length=None, **kwargs):
          """
          Create a Unicode-converting Text type.
  
          Parameters are the same as that of :class:`.Text`,
          with the exception that ``convert_unicode``
          defaults to ``True``.
  
          """
          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
  
      @property
      def python_type(self):
          return int
  
      @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: self.__class__,
                  Numeric: Numeric,
              },
              operators.mul: {
                  Interval: Interval,
                  Integer: self.__class__,
                  Numeric: Numeric,
              },
  # start Py2K
  #            operators.div: {
  #                Integer: self.__class__,
  #                Numeric: Numeric,
  #            },
  # end Py2K
              operators.truediv: {
                  Integer: self.__class__,
                  Numeric: Numeric,
              },
              operators.sub: {
                  Integer: self.__class__,
                  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.
  
      .. note::
  
         The `cdecimal <http://pypi.python.org/pypi/cdecimal/>`_ library
         is a high performing alternative to Python's built-in
         ``decimal.Decimal`` type, which performs very poorly in high volume
         situations. SQLAlchemy 0.7 is tested against ``cdecimal`` and supports
         it fully. The type is not necessarily supported by DBAPI
         implementations however, most of which contain an import for plain
         ``decimal`` in their source code, even though some such as psycopg2
         provide hooks for alternate adapters. SQLAlchemy imports ``decimal``
         globally as well.  The most straightforward and
         foolproof way to use "cdecimal" given current DBAPI and Python support
         is to patch it directly into sys.modules before anything else is
         imported::
  
             import sys
             import cdecimal
             sys.modules["decimal"] = cdecimal
  
         While the global patch is a little ugly, it's particularly
         important to use just one decimal library at a time since
         Python Decimal and cdecimal Decimal objects
         are not currently compatible *with each other*::
  
             >>> import cdecimal
             >>> import decimal
             >>> decimal.Decimal("10") == cdecimal.Decimal("10")
             False
  
         SQLAlchemy will provide more natural support of
         cdecimal if and when it becomes a standard part of Python
         installations and is supported by all DBAPIs.
  
      """
  
      __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 get_dbapi_type(self, dbapi):
          return dbapi.NUMBER
  
      @property
      def python_type(self):
          if self.asdecimal:
              return decimal.Decimal
          else:
              return float
  
      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(
                                  decimal.Decimal, self.scale)
                  else:
                      return processors.to_decimal_processor_factory(
                                  decimal.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: self.__class__,
                  Integer: self.__class__,
              },
  # start Py2K
  #            operators.div: {
  #                Numeric: self.__class__,
  #                Integer: self.__class__,
  #            },
  # end Py2K
              operators.truediv: {
                  Numeric: self.__class__,
                  Integer: self.__class__,
              },
              operators.add: {
                  Numeric: self.__class__,
                  Integer: self.__class__,
              },
              operators.sub: {
                  Numeric: self.__class__,
                  Integer: self.__class__,
              }
          }
  
  
  class Float(Numeric):
      """A type for ``float`` numbers.
  
      Returns Python ``float`` objects by default, applying
      conversion as needed.
  
      """
  
      __visit_name__ = 'float'
  
      scale = None
  
      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.
  
          :param \**kwargs: deprecated.  Additional arguments here are ignored
           by the default :class:`.Float` type.  For database specific
           floats that support additional arguments, see that dialect's
           documentation for details, such as
           :class:`sqlalchemy.dialects.mysql.FLOAT`.
  
          """
          self.precision = precision
          self.asdecimal = asdecimal
          if kwargs:
              util.warn_deprecated("Additional keyword arguments "
                                  "passed to Float ignored.")
  
      def result_processor(self, dialect, coltype):
          if self.asdecimal:
              return processors.to_decimal_processor_factory(decimal.Decimal)
          else:
              return None
  
      @util.memoized_property
      def _expression_adaptations(self):
          return {
              operators.mul: {
                  Interval: Interval,
                  Numeric: self.__class__,
              },
  # start Py2K
  #            operators.div: {
  #                Numeric: self.__class__,
  #            },
  # end Py2K
              operators.truediv: {
                  Numeric: self.__class__,
              },
              operators.add: {
                  Numeric: self.__class__,
              },
              operators.sub: {
                  Numeric: self.__class__,
              }
          }
  
  
  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):
          """Construct a new :class:`.DateTime`.
  
          :param 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.
  
          """
          self.timezone = timezone
  
      def get_dbapi_type(self, dbapi):
          return dbapi.DATETIME
  
      @property
      def python_type(self):
          return dt.datetime
  
      @util.memoized_property
      def _expression_adaptations(self):
          return {
              operators.add: {
                  Interval: self.__class__,
              },
              operators.sub: {
                  Interval: self.__class__,
                  DateTime: Interval,
              },
          }
  
  
  class Date(_DateAffinity, TypeEngine):
      """A type for ``datetime.date()`` objects."""
  
      __visit_name__ = 'date'
  
      def get_dbapi_type(self, dbapi):
          return dbapi.DATETIME
  
      @property
      def python_type(self):
          return dt.date
  
      @util.memoized_property
      def _expression_adaptations(self):
          return {
              operators.add: {
                  Integer: self.__class__,
                  Interval: DateTime,
                  Time: DateTime,
              },
              operators.sub: {
                  # date - integer = date
                  Integer: self.__class__,
  
                  # 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 get_dbapi_type(self, dbapi):
          return dbapi.DATETIME
  
      @property
      def python_type(self):
          return dt.time
  
      @util.memoized_property
      def _expression_adaptations(self):
          return {
              operators.add: {
                  Date: DateTime,
                  Interval: self.__class__
              },
              operators.sub: {
                  Time: Interval,
                  Interval: self.__class__,
              },
          }
  
  
  class _Binary(TypeEngine):
      """Define base behavior for binary types."""
  
      def __init__(self, length=None):
          self.length = length
  
      @property
      def python_type(self):
  # start Py3K
          return bytes
  # end Py3K
  # start Py2K
  #        return str
  # end Py2K
  
      # 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):
              x = self
              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,
      # psycopg2 as of 2.5 returns 'memoryview'
  # start Py3K
      def result_processor(self, dialect, coltype):
          def process(value):
              if value is not None:
                  value = bytes(value)
              return value
          return process
  # end Py3K
  # start 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:`.TypeEngine.coerce_compared_value` for a description."""
  
          if isinstance(value, str):
              return self
          else:
              return super(_Binary, self).coerce_compared_value(op, value)
  
      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(events.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.
  
      :class:`.SchemaType` classes can also be targets for the
      :meth:`.DDLEvents.before_parent_attach` and
      :meth:`.DDLEvents.after_parent_attach` events, where the events fire off
      surrounding the association of the type object with a parent
      :class:`.Column`.
  
      .. seealso::
  
          :class:`.Enum`
  
          :class:`.Boolean`
  
  
      """
  
      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)
          self.inherit_schema = kw.pop('inherit_schema', False)
          if self.metadata:
              event.listen(
                  self.metadata,
                  "before_create",
                  util.portable_instancemethod(self._on_metadata_create)
              )
              event.listen(
                  self.metadata,
                  "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, column, table):
          if self.inherit_schema:
              self.schema = table.schema
  
          event.listen(
              table,
              "before_create",
                util.portable_instancemethod(
                      self._on_table_create)
          )
          event.listen(
              table,
              "after_drop",
              util.portable_instancemethod(self._on_table_drop)
          )
          if self.metadata is None:
              # TODO: what's the difference between self.metadata
              # and table.metadata here ?
              event.listen(
                  table.metadata,
                  "before_create",
                  util.portable_instancemethod(self._on_metadata_create)
              )
              event.listen(
                  table.metadata,
                  "after_drop",
                  util.portable_instancemethod(self._on_metadata_drop)
              )
  
      def copy(self, **kw):
          return self.adapt(self.__class__)
  
      def adapt(self, impltype, **kw):
          schema = kw.pop('schema', self.schema)
          metadata = kw.pop('metadata', self.metadata)
          return impltype(name=self.name,
                      quote=self.quote,
                      schema=schema,
                      metadata=metadata,
                      inherit_schema=self.inherit_schema,
                      **kw
                      )
  
      @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.__class__ is not self.__class__ 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.__class__ is not self.__class__ and isinstance(t, SchemaType):
              t.drop(bind=bind, checkfirst=checkfirst)
  
      def _on_table_create(self, target, bind, **kw):
          t = self.dialect_impl(bind.dialect)
          if t.__class__ is not self.__class__ and isinstance(t, SchemaType):
              t._on_table_create(target, bind, **kw)
  
      def _on_table_drop(self, target, bind, **kw):
          t = self.dialect_impl(bind.dialect)
          if t.__class__ is not self.__class__ and isinstance(t, SchemaType):
              t._on_table_drop(target, bind, **kw)
  
      def _on_metadata_create(self, target, bind, **kw):
          t = self.dialect_impl(bind.dialect)
          if t.__class__ is not self.__class__ and isinstance(t, SchemaType):
              t._on_metadata_create(target, bind, **kw)
  
      def _on_metadata_drop(self, target, bind, **kw):
          t = self.dialect_impl(bind.dialect)
          if t.__class__ is not self.__class__ and isinstance(t, SchemaType):
              t._on_metadata_drop(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.
  
      .. seealso::
  
          :class:`~.postgresql.ENUM` - PostgreSQL-specific type,
          which has additional functionality.
  
      """
  
      __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: 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 :class:`.Enum` type does not
                  by default make use of the ``schema`` established on the
                  owning :class:`.Table`.  If this behavior is desired,
                  set the ``inherit_schema`` flag to ``True``.
  
          :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.
  
          :param inherit_schema: When ``True``, the "schema" from the owning
             :class:`.Table` will be copied to the "schema" attribute of this
             :class:`.Enum`, replacing whatever value was passed for the
             ``schema`` attribute.   This also takes effect when using the
             :meth:`.Table.tometadata` operation.
  
             .. versionadded:: 0.8
  
          """
          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, str):
                      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 __repr__(self):
          return util.generic_repr(self, [
                          ("native_enum", True),
                          ("name", None)
                      ])
  
      def _should_create_constraint(self, compiler):
          return not self.native_enum or \
                      not compiler.dialect.supports_native_enum
  
      def _set_table(self, column, table):
          if self.native_enum:
              SchemaType._set_table(self, column, table)
  
          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, **kw):
          schema = kw.pop('schema', self.schema)
          metadata = kw.pop('metadata', self.metadata)
          if issubclass(impltype, Enum):
              return impltype(name=self.name,
                          quote=self.quote,
                          schema=schema,
                          metadata=metadata,
                          convert_unicode=self.convert_unicode,
                          native_enum=self.native_enum,
                          inherit_schema=self.inherit_schema,
                          *self.enums,
                          **kw
                          )
          else:
              return super(Enum, self).adapt(impltype, **kw)
  
  
  class PickleType(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 :class:`.PickleType`, see :ref:`mutable_toplevel`.
  
      """
  
      impl = LargeBinary
  
      def __init__(self, protocol=pickle.HIGHEST_PROTOCOL,
                      pickler=None, 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 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.
  
          """
          self.protocol = protocol
          self.pickler = pickler or pickle
          self.comparator = comparator
          super(PickleType, self).__init__()
  
      def __reduce__(self):
          return PickleType, (self.protocol,
                              None,
                              self.comparator)
  
      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 compare_values(self, x, y):
          if self.comparator:
              return self.comparator(x, y)
          else:
              return x == y
  
  
  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, column, table):
          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)
  
      @property
      def python_type(self):
          return bool
  
      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, **kw):
          if self.native and hasattr(cls, '_adapt_from_generic_interval'):
              return cls._adapt_from_generic_interval(self, **kw)
          else:
              return self.__class__(
                          native=self.native,
                          second_precision=self.second_precision,
                          day_precision=self.day_precision,
                          **kw)
  
      @property
      def python_type(self):
          return dt.timedelta
  
      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: self.__class__,
                  DateTime: DateTime,
                  Time: Time,
              },
              operators.sub: {
                  Interval: self.__class__
              },
              operators.mul: {
                  Numeric: self.__class__
              },
              operators.truediv: {
                  Numeric: self.__class__
              },
  # start Py2K
  #            operators.div: {
  #                Numeric: self.__class__
  #            }
  # end Py2K
          }
  
      @property
      def _type_affinity(self):
          return Interval
  
      def coerce_compared_value(self, op, value):
          """See :meth:`.TypeEngine.coerce_compared_value` for a description."""
  
          return self.impl.coerce_compared_value(op, value)
  
  
  class REAL(Float):
      """The SQL REAL type."""
  
      __visit_name__ = 'REAL'
  
  
  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()
  
  _type_map = {
      str: String(),
  # start Py3K
      bytes: LargeBinary(),
  # end Py3K
  # start Py2K
  #    unicode: Unicode(),
  # end Py2K
      int: Integer(),
      float: Numeric(),
      bool: BOOLEANTYPE,
      decimal.Decimal: Numeric(),
      dt.date: Date(),
      dt.datetime: DateTime(),
      dt.time: Time(),
      dt.timedelta: Interval(),
      NoneType: NULLTYPE
  }
  
  