text: # sql/sqltypes.py
  # Copyright (C) 2005-2020 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
  
  """SQL specific types.
  
  """
  
  import codecs
  import datetime as dt
  import decimal
  import json
  
  from . import elements
  from . import operators
  from . import type_api
  from .base import _bind_or_error
  from .base import NO_ARG
  from .base import SchemaEventTarget
  from .elements import _defer_name
  from .elements import _literal_as_binds
  from .elements import quoted_name
  from .elements import Slice
  from .elements import TypeCoerce as type_coerce  # noqa
  from .type_api import Emulated
  from .type_api import NativeForEmulated  # noqa
  from .type_api import to_instance
  from .type_api import TypeDecorator
  from .type_api import TypeEngine
  from .type_api import Variant
  from .. import event
  from .. import exc
  from .. import inspection
  from .. import processors
  from .. import util
  from ..util import compat
  from ..util import pickle
  
  
  if util.jython:
      import array
  
  
  class _LookupExpressionAdapter(object):
  
      """Mixin expression adaptations based on lookup tables.
  
      These rules are currently used by the numeric, integer and date types
      which have detailed cross-expression coercion rules.
  
      """
  
      @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
              lookup = self.type._expression_adaptations.get(
                  op, self._blank_dict
              ).get(othertype, self.type)
              if lookup is othertype:
                  return (op, other_comparator.type)
              elif lookup is self.type._type_affinity:
                  return (op, self.type)
              else:
                  return (op, to_instance(lookup))
  
      comparator_factory = Comparator
  
  
  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 super(Concatenable.Comparator, self)._adapt_expression(
                      op, other_comparator
                  )
  
      comparator_factory = Comparator
  
  
  class Indexable(object):
      """A mixin that marks a type as supporting indexing operations,
      such as array or JSON structures.
  
  
      .. versionadded:: 1.1.0
  
  
      """
  
      class Comparator(TypeEngine.Comparator):
          def _setup_getitem(self, index):
              raise NotImplementedError()
  
          def __getitem__(self, index):
              (
                  adjusted_op,
                  adjusted_right_expr,
                  result_type,
              ) = self._setup_getitem(index)
              return self.operate(
                  adjusted_op, adjusted_right_expr, result_type=result_type
              )
  
      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"
  
      @util.deprecated_params(
          convert_unicode=(
              "1.3",
              "The :paramref:`.String.convert_unicode` parameter is deprecated "
              "and will be removed in a future release.  All modern DBAPIs "
              "now support Python Unicode directly and this parameter is "
              "unnecessary.",
          ),
          unicode_error=(
              "1.3",
              "The :paramref:`.String.unicode_errors` parameter is deprecated "
              "and will be removed in a future release.  This parameter is "
              "unnecessary for modern Python DBAPIs and degrades performance "
              "significantly.",
          ),
      )
      def __init__(
          self,
          length=None,
          collation=None,
          convert_unicode=False,
          unicode_error=None,
          _warn_on_bytestring=False,
          _expect_unicode=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
  
          :param convert_unicode: When set to ``True``, the
            :class:`.String` type will assume that
            input is to be passed as Python Unicode objects under Python 2,
            and results returned as Python Unicode objects.
            In the rare circumstance that the DBAPI does not support
            Python unicode under Python 2, SQLAlchemy will use its own
            encoder/decoder functionality on strings, referring to the
            value of the :paramref:`.create_engine.encoding` parameter
            parameter passed to :func:`.create_engine` as the encoding.
  
            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 string value ``"force"`` can be passed here which will
            cause SQLAlchemy's encode/decode services to be
            used unconditionally.
  
            .. note::
  
              SQLAlchemy's unicode-conversion flags and features only apply
              to Python 2; in Python 3, all string objects are Unicode objects.
              For this reason, as well as the fact that virtually all modern
              DBAPIs now support Unicode natively even under Python 2,
              the :paramref:`.String.convert_unicode` flag is inherently a
              legacy feature.
  
            .. note::
  
              In the vast majority of cases, the :class:`.Unicode` or
              :class:`.UnicodeText` datatypes should be used for a
              :class:`.Column` that expects to store non-ascii data.  These
              datatypes will ensure that the correct types are used on the
              database side as well as set up the correct Unicode behaviors
              under Python 2.
  
            .. seealso::
  
              :paramref:`.create_engine.convert_unicode` -
              :class:`.Engine`-wide parameter
  
          :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, requires
            that :paramref:`.String.convert_unicode` is set to
            ``"force"``
  
          """
          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._expect_unicode = convert_unicode or _expect_unicode
          self._expect_unicode_error = unicode_error
  
          self._warn_on_bytestring = _warn_on_bytestring
  
      def literal_processor(self, dialect):
          def process(value):
              value = value.replace("'", "''")
  
              if dialect.identifier_preparer._double_percents:
                  value = value.replace("%", "%%")
  
              return "'%s'" % value
  
          return process
  
      def bind_processor(self, dialect):
          if self._expect_unicode or dialect.convert_unicode:
              if (
                  dialect.supports_unicode_binds
                  and self._expect_unicode != "force"
              ):
                  if self._warn_on_bytestring:
  
                      def process(value):
                          if isinstance(value, util.binary_type):
                              util.warn_limited(
                                  "Unicode type received non-unicode "
                                  "bind param value %r.",
                                  (util.ellipses_string(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, util.text_type):
                          return encoder(value, self._expect_unicode_error)[0]
                      elif warn_on_bytestring and value is not None:
                          util.warn_limited(
                              "Unicode type received non-unicode bind "
                              "param value %r.",
                              (util.ellipses_string(value),),
                          )
                      return value
  
              return process
          else:
              return None
  
      def result_processor(self, dialect, coltype):
          wants_unicode = self._expect_unicode or dialect.convert_unicode
          needs_convert = wants_unicode and (
              dialect.returns_unicode_strings is not True
              or self._expect_unicode in ("force", "force_nocheck")
          )
          needs_isinstance = (
              needs_convert
              and dialect.returns_unicode_strings
              and self._expect_unicode != "force_nocheck"
          )
          if needs_convert:
              if needs_isinstance:
                  return processors.to_conditional_unicode_processor_factory(
                      dialect.encoding, self._expect_unicode_error
                  )
              else:
                  return processors.to_unicode_processor_factory(
                      dialect.encoding, self._expect_unicode_error
                  )
          else:
              return None
  
      @property
      def python_type(self):
          if self._expect_unicode:
              return util.text_type
          else:
              return str
  
      def get_dbapi_type(self, dbapi):
          return dbapi.STRING
  
      @classmethod
      def _warn_deprecated_unicode(cls):
          util.warn_deprecated(
              "The convert_unicode on Engine and String as well as the "
              "unicode_error flag on String are deprecated.  All modern "
              "DBAPIs now support Python Unicode natively under Python 2, and "
              "under Python 3 all strings are inherently Unicode.  These flags "
              "will be removed in a future release."
          )
  
  
  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.
  
      .. seealso::
  
          :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("_expect_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("_expect_unicode", True)
          kwargs.setdefault("_warn_on_bytestring", True)
          super(UnicodeText, self).__init__(length=length, **kwargs)
  
      def _warn_deprecated_unicode(self):
          pass
  
  
  class Integer(_LookupExpressionAdapter, 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
  
      def literal_processor(self, dialect):
          def process(value):
              return str(value)
  
          return process
  
      @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,
              },
              operators.div: {Integer: self.__class__, Numeric: Numeric},
              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(_LookupExpressionAdapter, TypeEngine):
  
      """A type for fixed precision numbers, such as ``NUMERIC`` or ``DECIMAL``.
  
      This type returns Python ``decimal.Decimal`` objects by default, unless
      the :paramref:`.Numeric.asdecimal` flag is set to False, in which case
      they are coerced to Python ``float`` objects.
  
      .. note::
  
          The :class:`.Numeric` type is designed to receive data from a database
          type that is explicitly known to be a decimal type
          (e.g. ``DECIMAL``, ``NUMERIC``, others) and not a floating point
          type (e.g. ``FLOAT``, ``REAL``, others).
          If the database column on the server is in fact a floating-point type
          type, such as ``FLOAT`` or ``REAL``, use the :class:`.Float`
          type or a subclass, otherwise numeric coercion between
          ``float``/``Decimal`` may or may not function as expected.
  
      .. note::
  
         The Python ``decimal.Decimal`` class is generally slow
         performing; cPython 3.3 has now switched to use the `cdecimal
         <http://pypi.python.org/pypi/cdecimal/>`_ library natively. For
         older Python versions, the ``cdecimal`` library can be patched
         into any application where it will replace the ``decimal``
         library fully, however this needs to be applied globally and
         before any other modules have been imported, as follows::
  
             import sys
             import cdecimal
             sys.modules["decimal"] = cdecimal
  
         Note that the ``cdecimal`` and ``decimal`` libraries are **not
         compatible with each other**, so patching ``cdecimal`` at the
         global level is the only way it can be used effectively with
         various DBAPIs that hardcode to import the ``decimal`` library.
  
      """
  
      __visit_name__ = "numeric"
  
      _default_decimal_return_scale = 10
  
      def __init__(
          self,
          precision=None,
          scale=None,
          decimal_return_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.
  
          :param decimal_return_scale: Default scale to use when converting
           from floats to Python decimals.  Floating point values will typically
           be much longer due to decimal inaccuracy, and most floating point
           database types don't have a notion of "scale", so by default the
           float type looks for the first ten decimal places when converting.
           Specifying this value will override that length.  Types which
           do include an explicit ".scale" value, such as the base
           :class:`.Numeric` as well as the MySQL float types, will use the
           value of ".scale" as the default for decimal_return_scale, if not
           otherwise specified.
  
           .. versionadded:: 0.9.0
  
          When using the ``Numeric`` type, care should be taken to ensure
          that the asdecimal setting is appropriate 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.decimal_return_scale = decimal_return_scale
          self.asdecimal = asdecimal
  
      @property
      def _effective_decimal_return_scale(self):
          if self.decimal_return_scale is not None:
              return self.decimal_return_scale
          elif getattr(self, "scale", None) is not None:
              return self.scale
          else:
              return self._default_decimal_return_scale
  
      def get_dbapi_type(self, dbapi):
          return dbapi.NUMBER
  
      def literal_processor(self, dialect):
          def process(value):
              return str(value)
  
          return process
  
      @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.
                  return processors.to_decimal_processor_factory(
                      decimal.Decimal,
                      self.scale
                      if self.scale is not None
                      else self._default_decimal_return_scale,
                  )
          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__,
              },
              operators.div: {Numeric: self.__class__, Integer: self.__class__},
              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):
  
      """Type representing floating point types, such as ``FLOAT`` or ``REAL``.
  
      This type returns Python ``float`` objects by default, unless the
      :paramref:`.Float.asdecimal` flag is set to True, in which case they
      are coerced to ``decimal.Decimal`` objects.
  
      .. note::
  
          The :class:`.Float` type is designed to receive data from a database
          type that is explicitly known to be a floating point type
          (e.g. ``FLOAT``, ``REAL``, others)
          and not a decimal type (e.g. ``DECIMAL``, ``NUMERIC``, others).
          If the database column on the server is in fact a Numeric
          type, such as ``DECIMAL`` or ``NUMERIC``, use the :class:`.Numeric`
          type or a subclass, otherwise numeric coercion between
          ``float``/``Decimal`` may or may not function as expected.
  
      """
  
      __visit_name__ = "float"
  
      scale = None
  
      def __init__(
          self, precision=None, asdecimal=False, decimal_return_scale=None
      ):
          r"""
          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 decimal_return_scale: Default scale to use when converting
           from floats to Python decimals.  Floating point values will typically
           be much longer due to decimal inaccuracy, and most floating point
           database types don't have a notion of "scale", so by default the
           float type looks for the first ten decimal places when converting.
           Specifying this value will override that length.  Note that the
           MySQL float types, which do include "scale", will use "scale"
           as the default for decimal_return_scale, if not otherwise specified.
  
           .. versionadded:: 0.9.0
  
          """
          self.precision = precision
          self.asdecimal = asdecimal
          self.decimal_return_scale = decimal_return_scale
  
      def result_processor(self, dialect, coltype):
          if self.asdecimal:
              return processors.to_decimal_processor_factory(
                  decimal.Decimal, self._effective_decimal_return_scale
              )
          elif dialect.supports_native_decimal:
              return processors.to_float
          else:
              return None
  
  
  class DateTime(_LookupExpressionAdapter, 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.
  
      For the time representation within the datetime type, some
      backends include additional options, such as timezone support and
      fractional seconds support.  For fractional seconds, use the
      dialect-specific datatype, such as :class:`.mysql.TIME`.  For
      timezone support, use at least the :class:`~.types.TIMESTAMP` datatype,
      if not the dialect-specific datatype object.
  
      """
  
      __visit_name__ = "datetime"
  
      def __init__(self, timezone=False):
          """Construct a new :class:`.DateTime`.
  
          :param timezone: boolean.  Indicates that the datetime type should
           enable timezone support, if available on the
           **base date/time-holding type only**.   It is recommended
           to make use of the :class:`~.types.TIMESTAMP` datatype directly when
           using this flag, as some databases include separate generic
           date/time-holding types distinct from the timezone-capable
           TIMESTAMP datatype, such as Oracle.
  
  
          """
          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):
  
          # Based on http://www.postgresql.org/docs/current/\
          # static/functions-datetime.html.
  
          return {
              operators.add: {Interval: self.__class__},
              operators.sub: {Interval: self.__class__, DateTime: Interval},
          }
  
  
  class Date(_LookupExpressionAdapter, 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):
          # Based on http://www.postgresql.org/docs/current/\
          # static/functions-datetime.html.
  
          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(_LookupExpressionAdapter, 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):
          # Based on http://www.postgresql.org/docs/current/\
          # static/functions-datetime.html.
  
          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
  
      def literal_processor(self, dialect):
          def process(value):
              value = value.decode(dialect.encoding).replace("'", "''")
              return "'%s'" % value
  
          return process
  
      @property
      def python_type(self):
          return util.binary_type
  
      # Python 3 - sqlite3 doesn't need the `Binary` conversion
      # here, though pg8000 does to indicate "bytea"
      def bind_processor(self, dialect):
          if dialect.dbapi is None:
              return None
  
          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,
      # psycopg2 as of 2.5 returns 'memoryview'
      if util.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
  
      else:
  
          def result_processor(self, dialect, coltype):
              def process(value):
                  if value is not None:
                      value = bytes(value)
                  return value
  
              return process
  
      def coerce_compared_value(self, op, value):
          """See :meth:`.TypeEngine.coerce_compared_value` for a description."""
  
          if isinstance(value, util.string_types):
              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 :class:`.LargeBinary` type corresponds to a large and/or unlengthed
      binary type for the target platform, such as BLOB on MySQL and BYTEA for
      PostgreSQL.  It also handles the necessary conversions for the DBAPI.
  
      """
  
      __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 binary types that accept a length,
            such as the MySQL BLOB type.
  
          """
          _Binary.__init__(self, length=length)
  
  
  @util.deprecated_cls(
      "0.6",
      "The :class:`.Binary` class is deprecated and will be removed "
      "in a future relase.  Please use :class:`.LargeBinary`.",
  )
  class Binary(LargeBinary):
      def __init__(self, *arg, **kw):
          LargeBinary.__init__(self, *arg, **kw)
  
  
  class SchemaType(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,
          name=None,
          schema=None,
          metadata=None,
          inherit_schema=False,
          quote=None,
          _create_events=True,
      ):
          if name is not None:
              self.name = quoted_name(name, quote)
          else:
              self.name = None
          self.schema = schema
          self.metadata = metadata
          self.inherit_schema = inherit_schema
          self._create_events = _create_events
  
          if _create_events and 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 _translate_schema(self, effective_schema, map_):
          return map_.get(effective_schema, effective_schema)
  
      def _set_parent(self, column):
          column._on_table_attach(util.portable_instancemethod(self._set_table))
  
      def _variant_mapping_for_set_table(self, column):
          if isinstance(column.type, Variant):
              variant_mapping = column.type.mapping.copy()
              variant_mapping["_default"] = column.type.impl
          else:
              variant_mapping = None
          return variant_mapping
  
      def _set_table(self, column, table):
          if self.inherit_schema:
              self.schema = table.schema
  
          if not self._create_events:
              return
  
          variant_mapping = self._variant_mapping_for_set_table(column)
  
          event.listen(
              table,
              "before_create",
              util.portable_instancemethod(
                  self._on_table_create, {"variant_mapping": variant_mapping}
              ),
          )
          event.listen(
              table,
              "after_drop",
              util.portable_instancemethod(
                  self._on_table_drop, {"variant_mapping": variant_mapping}
              ),
          )
          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,
                      {"variant_mapping": variant_mapping},
                  ),
              )
              event.listen(
                  table.metadata,
                  "after_drop",
                  util.portable_instancemethod(
                      self._on_metadata_drop,
                      {"variant_mapping": variant_mapping},
                  ),
              )
  
      def copy(self, **kw):
          return self.adapt(self.__class__, _create_events=True)
  
      def adapt(self, impltype, **kw):
          schema = kw.pop("schema", self.schema)
          metadata = kw.pop("metadata", self.metadata)
          _create_events = kw.pop("_create_events", False)
          return impltype(
              name=self.name,
              schema=schema,
              inherit_schema=self.inherit_schema,
              metadata=metadata,
              _create_events=_create_events,
              **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 = _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 = _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):
          if not self._is_impl_for_variant(bind.dialect, kw):
              return
  
          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):
          if not self._is_impl_for_variant(bind.dialect, kw):
              return
  
          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):
          if not self._is_impl_for_variant(bind.dialect, kw):
              return
  
          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):
          if not self._is_impl_for_variant(bind.dialect, kw):
              return
  
          t = self.dialect_impl(bind.dialect)
          if t.__class__ is not self.__class__ and isinstance(t, SchemaType):
              t._on_metadata_drop(target, bind, **kw)
  
      def _is_impl_for_variant(self, dialect, kw):
          variant_mapping = kw.pop("variant_mapping", None)
          if variant_mapping is None:
              return True
  
          if (
              dialect.name in variant_mapping
              and variant_mapping[dialect.name] is self
          ):
              return True
          elif dialect.name not in variant_mapping:
              return variant_mapping["_default"] is self
  
  
  class Enum(Emulated, String, SchemaType):
      """Generic Enum Type.
  
      The :class:`.Enum` type provides a set of possible string values
      which the column is constrained towards.
  
      The :class:`.Enum` type will make use of the backend's native "ENUM"
      type if one is available; otherwise, it uses a VARCHAR datatype and
      produces a CHECK constraint.  Use of the backend-native enum type
      can be disabled using the :paramref:`.Enum.native_enum` flag, and
      the production of the CHECK constraint is configurable using the
      :paramref:`.Enum.create_constraint` flag.
  
      The :class:`.Enum` type also provides in-Python validation of string
      values during both read and write operations.  When reading a value
      from the database in a result set, the string value is always checked
      against the list of possible values and a ``LookupError`` is raised
      if no match is found.  When passing a value to the database as a
      plain string within a SQL statement, if the
      :paramref:`.Enum.validate_strings` parameter is
      set to True, a ``LookupError`` is raised for any string value that's
      not located in the given list of possible values; note that this
      impacts usage of LIKE expressions with enumerated values (an unusual
      use case).
  
      .. versionchanged:: 1.1 the :class:`.Enum` type now provides in-Python
         validation of input values as well as on data being returned by
         the database.
  
      The source of enumerated values may be a list of string values, or
      alternatively a PEP-435-compliant enumerated class.  For the purposes
      of the :class:`.Enum` datatype, this class need only provide a
      ``__members__`` method.
  
      When using an enumerated class, the enumerated objects are used
      both for input and output, rather than strings as is the case with
      a plain-string enumerated type::
  
          import enum
          class MyEnum(enum.Enum):
              one = 1
              two = 2
              three = 3
  
          t = Table(
              'data', MetaData(),
              Column('value', Enum(MyEnum))
          )
  
          connection.execute(t.insert(), {"value": MyEnum.two})
          assert connection.scalar(t.select()) is MyEnum.two
  
      Above, the string names of each element, e.g. "one", "two", "three",
      are persisted to the database; the values of the Python Enum, here
      indicated as integers, are **not** used; the value of each enum can
      therefore be any kind of Python object whether or not it is persistable.
  
      In order to persist the values and not the names, the
      :paramref:`.Enum.values_callable` parameter may be used.   The value of
      this parameter is a user-supplied callable, which  is intended to be used
      with a PEP-435-compliant enumerated class and  returns a list of string
      values to be persisted.   For a simple enumeration that uses string values,
      a callable such as  ``lambda x: [e.value for e in x]`` is sufficient.
  
      .. versionadded:: 1.1 - support for PEP-435-style enumerated
         classes.
  
  
      .. seealso::
  
          :class:`.postgresql.ENUM` - PostgreSQL-specific type,
          which has additional functionality.
  
          :class:`.mysql.ENUM` - MySQL-specific type
  
      """
  
      __visit_name__ = "enum"
  
      @util.deprecated_params(
          convert_unicode=(
              "1.3",
              "The :paramref:`.Enum.convert_unicode` parameter is deprecated "
              "and will be removed in a future release.  All modern DBAPIs "
              "now support Python Unicode directly and this parameter is "
              "unnecessary.",
          )
      )
      def __init__(self, *enums, **kw):
          r"""Construct an enum.
  
          Keyword arguments which don't apply to a specific backend are ignored
          by that backend.
  
          :param \*enums: either exactly one PEP-435 compliant enumerated type
             or one or more string or unicode enumeration labels. If unicode
             labels are present, the `convert_unicode` flag is auto-enabled.
  
             .. versionadded:: 1.1 a PEP-435 style enumerated class may be
                passed.
  
          :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 create_constraint: defaults to True.  When creating a non-native
             enumerated type, also build a CHECK constraint on the database
             against the valid values.
  
             .. versionadded:: 1.1 - added :paramref:`.Enum.create_constraint`
                which provides the option to disable the production of the
                CHECK constraint for a non-native enumerated type.
  
          :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 its 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. If a PEP-435 enumerated
             class was used, its name (converted to lower case) is used by
             default.
  
          :param native_enum: Use the database's native ENUM type when
             available. Defaults to True. When False, uses VARCHAR + check
             constraint for all backends. The VARCHAR length can be controlled
             with :paramref:`.Enum.length`
  
          :param length: Allows specifying a custom length for the VARCHAR
             when :paramref:`.Enum.native_enum` is False. By default it uses the
             length of the longest value.
  
             .. versionadded:: 1.3.16
  
          :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: Set explicit quoting preferences for the type's name.
  
          :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.
  
          :param validate_strings: when True, string values that are being
             passed to the database in a SQL statement will be checked
             for validity against the list of enumerated values.  Unrecognized
             values will result in a ``LookupError`` being raised.
  
             .. versionadded:: 1.1.0b2
  
          :param values_callable: A callable which will be passed the PEP-435
             compliant enumerated type, which should then return a list of string
             values to be persisted. This allows for alternate usages such as
             using the string value of an enum to be persisted to the database
             instead of its name.
  
             .. versionadded:: 1.2.3
  
          :param sort_key_function: a Python callable which may be used as the
             "key" argument in the Python ``sorted()`` built-in.   The SQLAlchemy
             ORM requires that primary key columns which are mapped must
             be sortable in some way.  When using an unsortable enumeration
             object such as a Python 3 ``Enum`` object, this parameter may be
             used to set a default sort key function for the objects.  By
             default, the database value of the enumeration is used as the
             sorting function.
  
              .. versionadded:: 1.3.8
  
  
  
          """
          self._enum_init(enums, kw)
  
      @property
      def _enums_argument(self):
          if self.enum_class is not None:
              return [self.enum_class]
          else:
              return self.enums
  
      def _enum_init(self, enums, kw):
          """internal init for :class:`.Enum` and subclasses.
  
          friendly init helper used by subclasses to remove
          all the Enum-specific keyword arguments from kw.  Allows all
          other arguments in kw to pass through.
  
          """
          self.native_enum = kw.pop("native_enum", True)
          self.create_constraint = kw.pop("create_constraint", True)
          self.values_callable = kw.pop("values_callable", None)
          self._sort_key_function = kw.pop("sort_key_function", NO_ARG)
          length_arg = kw.pop("length", NO_ARG)
  
          values, objects = self._parse_into_values(enums, kw)
          self._setup_for_values(values, objects, kw)
  
          convert_unicode = kw.pop("convert_unicode", None)
          self.validate_strings = kw.pop("validate_strings", False)
  
          if convert_unicode is None:
              for e in self.enums:
                  # this is all py2k logic that can go away for py3k only,
                  # "expect unicode" will always be implicitly true
                  if isinstance(e, util.text_type):
                      _expect_unicode = True
                      break
              else:
                  _expect_unicode = False
          else:
              _expect_unicode = convert_unicode
  
          if self.enums:
              length = max(len(x) for x in self.enums)
          else:
              length = 0
          if not self.native_enum and length_arg is not NO_ARG:
              if length_arg < length:
                  raise ValueError(
                      "When provided, length must be larger or equal"
                      " than the length of the longest enum value. %s < %s"
                      % (length_arg, length)
                  )
              length = length_arg
  
          self._valid_lookup[None] = self._object_lookup[None] = None
  
          super(Enum, self).__init__(
              length=length, _expect_unicode=_expect_unicode
          )
  
          if self.enum_class:
              kw.setdefault("name", self.enum_class.__name__.lower())
          SchemaType.__init__(
              self,
              name=kw.pop("name", None),
              schema=kw.pop("schema", None),
              metadata=kw.pop("metadata", None),
              inherit_schema=kw.pop("inherit_schema", False),
              quote=kw.pop("quote", None),
              _create_events=kw.pop("_create_events", True),
          )
  
      def _parse_into_values(self, enums, kw):
          if not enums and "_enums" in kw:
              enums = kw.pop("_enums")
  
          if len(enums) == 1 and hasattr(enums[0], "__members__"):
              self.enum_class = enums[0]
              members = self.enum_class.__members__
              if self.values_callable:
                  values = self.values_callable(self.enum_class)
              else:
                  values = list(members)
              objects = [members[k] for k in members]
              return values, objects
          else:
              self.enum_class = None
              return enums, enums
  
      def _setup_for_values(self, values, objects, kw):
          self.enums = list(values)
  
          self._valid_lookup = dict(zip(reversed(objects), reversed(values)))
  
          self._object_lookup = dict(zip(values, objects))
  
          self._valid_lookup.update(
              [
                  (value, self._valid_lookup[self._object_lookup[value]])
                  for value in values
              ]
          )
  
      @property
      def sort_key_function(self):
          if self._sort_key_function is NO_ARG:
              return self._db_value_for_elem
          else:
              return self._sort_key_function
  
      @property
      def native(self):
          return self.native_enum
  
      def _db_value_for_elem(self, elem):
          try:
              return self._valid_lookup[elem]
          except KeyError as err:
              # for unknown string values, we return as is.  While we can
              # validate these if we wanted, that does not allow for lesser-used
              # end-user use cases, such as using a LIKE comparison with an enum,
              # or for an application that wishes to apply string tests to an
              # ENUM (see [ticket:3725]).  While we can decide to differentiate
              # here between an INSERT statement and a criteria used in a SELECT,
              # for now we're staying conservative w/ behavioral changes (perhaps
              # someone has a trigger that handles strings on INSERT)
              if not self.validate_strings and isinstance(
                  elem, compat.string_types
              ):
                  return elem
              else:
                  util.raise_(
                      LookupError(
                          '"%s" is not among the defined enum values' % elem
                      ),
                      replace_context=err,
                  )
  
      class Comparator(String.Comparator):
          def _adapt_expression(self, op, other_comparator):
              op, typ = super(Enum.Comparator, self)._adapt_expression(
                  op, other_comparator
              )
              if op is operators.concat_op:
                  typ = String(
                      self.type.length, _expect_unicode=self.type._expect_unicode
                  )
              return op, typ
  
      comparator_factory = Comparator
  
      def _object_value_for_elem(self, elem):
          try:
              return self._object_lookup[elem]
          except KeyError as err:
              util.raise_(
                  LookupError(
                      '"%s" is not among the defined enum values' % elem
                  ),
                  replace_context=err,
              )
  
      def __repr__(self):
          return util.generic_repr(
              self,
              additional_kw=[("native_enum", True)],
              to_inspect=[Enum, SchemaType],
          )
  
      def adapt_to_emulated(self, impltype, **kw):
          kw.setdefault("_expect_unicode", self._expect_unicode)
          kw.setdefault("validate_strings", self.validate_strings)
          kw.setdefault("name", self.name)
          kw.setdefault("schema", self.schema)
          kw.setdefault("inherit_schema", self.inherit_schema)
          kw.setdefault("metadata", self.metadata)
          kw.setdefault("_create_events", False)
          kw.setdefault("native_enum", self.native_enum)
          kw.setdefault("values_callable", self.values_callable)
          kw.setdefault("create_constraint", self.create_constraint)
          kw.setdefault("length", self.length)
          assert "_enums" in kw
          return impltype(**kw)
  
      def adapt(self, impltype, **kw):
          kw["_enums"] = self._enums_argument
          return super(Enum, self).adapt(impltype, **kw)
  
      def _should_create_constraint(self, compiler, **kw):
          if not self._is_impl_for_variant(compiler.dialect, kw):
              return False
          return (
              not self.native_enum or not compiler.dialect.supports_native_enum
          )
  
      @util.dependencies("sqlalchemy.sql.schema")
      def _set_table(self, schema, column, table):
          SchemaType._set_table(self, column, table)
  
          if not self.create_constraint:
              return
  
          variant_mapping = self._variant_mapping_for_set_table(column)
  
          e = schema.CheckConstraint(
              type_coerce(column, self).in_(self.enums),
              name=_defer_name(self.name),
              _create_rule=util.portable_instancemethod(
                  self._should_create_constraint,
                  {"variant_mapping": variant_mapping},
              ),
              _type_bound=True,
          )
          assert e.table is table
  
      def literal_processor(self, dialect):
          parent_processor = super(Enum, self).literal_processor(dialect)
  
          def process(value):
              value = self._db_value_for_elem(value)
              if parent_processor:
                  value = parent_processor(value)
              return value
  
          return process
  
      def bind_processor(self, dialect):
          def process(value):
              value = self._db_value_for_elem(value)
              if parent_processor:
                  value = parent_processor(value)
              return value
  
          parent_processor = super(Enum, self).bind_processor(dialect)
          return process
  
      def result_processor(self, dialect, coltype):
          parent_processor = super(Enum, self).result_processor(dialect, coltype)
  
          def process(value):
              if parent_processor:
                  value = parent_processor(value)
  
              value = self._object_value_for_elem(value)
              return value
  
          return process
  
      def copy(self, **kw):
          return SchemaType.copy(self, **kw)
  
      @property
      def python_type(self):
          if self.enum_class:
              return self.enum_class
          else:
              return super(Enum, self).python_type
  
  
  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(Emulated, TypeEngine, SchemaType):
  
      """A bool datatype.
  
      :class:`.Boolean` typically uses BOOLEAN or SMALLINT on the DDL side,
      and on the Python side deals in ``True`` or ``False``.
  
      The :class:`.Boolean` datatype currently has two levels of assertion
      that the values persisted are simple true/false values.  For all
      backends, only the Python values ``None``, ``True``, ``False``, ``1``
      or ``0`` are accepted as parameter values.   For those backends that
      don't support a "native boolean" datatype, a CHECK constraint is also
      created on the target column.   Production of the CHECK constraint
      can be disabled by passing the :paramref:`.Boolean.create_constraint`
      flag set to ``False``.
  
      .. versionchanged:: 1.2 the :class:`.Boolean` datatype now asserts that
         incoming Python values are already in pure boolean form.
  
  
      """
  
      __visit_name__ = "boolean"
      native = True
  
      def __init__(self, create_constraint=True, name=None, _create_events=True):
          """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
          self._create_events = _create_events
  
      def _should_create_constraint(self, compiler, **kw):
          if not self._is_impl_for_variant(compiler.dialect, kw):
              return False
          return (
              not compiler.dialect.supports_native_boolean
              and compiler.dialect.non_native_boolean_check_constraint
          )
  
      @util.dependencies("sqlalchemy.sql.schema")
      def _set_table(self, schema, column, table):
          if not self.create_constraint:
              return
  
          variant_mapping = self._variant_mapping_for_set_table(column)
  
          e = schema.CheckConstraint(
              type_coerce(column, self).in_([0, 1]),
              name=_defer_name(self.name),
              _create_rule=util.portable_instancemethod(
                  self._should_create_constraint,
                  {"variant_mapping": variant_mapping},
              ),
              _type_bound=True,
          )
          assert e.table is table
  
      @property
      def python_type(self):
          return bool
  
      _strict_bools = frozenset([None, True, False])
  
      def _strict_as_bool(self, value):
          if value not in self._strict_bools:
              if not isinstance(value, int):
                  raise TypeError("Not a boolean value: %r" % value)
              else:
                  raise ValueError(
                      "Value %r is not None, True, or False" % value
                  )
          return value
  
      def literal_processor(self, dialect):
          compiler = dialect.statement_compiler(dialect, None)
          true = compiler.visit_true(None)
          false = compiler.visit_false(None)
  
          def process(value):
              return true if self._strict_as_bool(value) else false
  
          return process
  
      def bind_processor(self, dialect):
          _strict_as_bool = self._strict_as_bool
          if dialect.supports_native_boolean:
              _coerce = bool
          else:
              _coerce = int
  
          def process(value):
              value = _strict_as_bool(value)
              if value is not None:
                  value = _coerce(value)
              return value
  
          return process
  
      def result_processor(self, dialect, coltype):
          if dialect.supports_native_boolean:
              return None
          else:
              return processors.int_to_boolean
  
  
  class _AbstractInterval(_LookupExpressionAdapter, TypeEngine):
      @util.memoized_property
      def _expression_adaptations(self):
          # Based on http://www.postgresql.org/docs/current/\
          # static/functions-datetime.html.
  
          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__},
              operators.div: {Numeric: self.__class__},
          }
  
      @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 Interval(Emulated, _AbstractInterval, 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
  
      @property
      def python_type(self):
          return dt.timedelta
  
      def adapt_to_emulated(self, impltype, **kw):
          return _AbstractInterval.adapt(self, impltype, **kw)
  
      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
  
  
  class JSON(Indexable, TypeEngine):
      """Represent a SQL JSON type.
  
      .. note::  :class:`.types.JSON` is provided as a facade for vendor-specific
         JSON types.  Since it supports JSON SQL operations, it only
         works on backends that have an actual JSON type, currently:
  
         * PostgreSQL
  
         * MySQL as of version 5.7 (MariaDB as of the 10.2 series does not)
  
         * SQLite as of version 3.9
  
      :class:`.types.JSON` is part of the Core in support of the growing
      popularity of native JSON datatypes.
  
      The :class:`.types.JSON` type stores arbitrary JSON format data, e.g.::
  
          data_table = Table('data_table', metadata,
              Column('id', Integer, primary_key=True),
              Column('data', JSON)
          )
  
          with engine.connect() as conn:
              conn.execute(
                  data_table.insert(),
                  data = {"key1": "value1", "key2": "value2"}
              )
  
      **JSON-Specific Expression Operators**
  
      The :class:`.types.JSON` datatype provides these additional SQL operations:
  
      * Keyed index operations::
  
          data_table.c.data['some key']
  
      * Integer index operations::
  
          data_table.c.data[3]
  
      * Path index operations::
  
          data_table.c.data[('key_1', 'key_2', 5, ..., 'key_n')]
  
      * Data casters for specific JSON element types, subsequent to an index
        or path operation being invoked::
  
          data_table.c.data["some key"].as_integer()
  
        .. versionadded:: 1.3.11
  
      Additional operations may be available from the dialect-specific versions
      of :class:`.types.JSON`, such as :class:`.postgresql.JSON` and
      :class:`.postgresql.JSONB` which both offer additional PostgreSQL-specific
      operations.
  
      **Casting JSON Elements to Other Types**
  
      Index operations, i.e. those invoked by calling upon the expression using
      the Python bracket operator as in ``some_column['some key']``, return an
      expression object whose type defaults to :class:`.JSON` by default, so that
      further JSON-oriented instructions may be called upon the result type.
      However, it is likely more common that an index operation is expected
      to return a specific scalar element, such as a string or integer.  In
      order to provide access to these elements in a backend-agnostic way,
      a series of data casters are provided:
  
      * :meth:`.JSON.Comparator.as_string` - return the element as a string
  
      * :meth:`.JSON.Comparator.as_boolean` - return the element as a boolean
  
      * :meth:`.JSON.Comparator.as_float` - return the element as a float
  
      * :meth:`.JSON.Comparator.as_integer` - return the element as an integer
  
      These data casters are implemented by supporting dialects in order to
      assure that comparisons to the above types will work as expected, such as::
  
          # integer comparison
          data_table.c.data["some_integer_key"].as_integer() == 5
  
          # boolean comparison
          data_table.c.data["some_boolean"].as_boolean() == True
  
      .. versionadded:: 1.3.11 Added type-specific casters for the basic JSON
         data element types.
  
      .. note::
  
          The data caster functions are new in version 1.3.11, and supersede
          the previous documented approaches of using CAST; for reference,
          this looked like::
  
             from sqlalchemy import cast, type_coerce
             from sqlalchemy import String, JSON
             cast(
                 data_table.c.data['some_key'], String
             ) == type_coerce(55, JSON)
  
          The above case now works directly as::
  
              data_table.c.data['some_key'].as_integer() == 5
  
          For details on the previous comparison approach within the 1.3.x
          series, see the documentation for SQLAlchemy 1.2 or the included HTML
          files in the doc/ directory of the version's distribution.
  
      **Detecting Changes in JSON columns when using the ORM**
  
      The :class:`.JSON` type, when used with the SQLAlchemy ORM, does not
      detect in-place mutations to the structure.  In order to detect these, the
      :mod:`sqlalchemy.ext.mutable` extension must be used.  This extension will
      allow "in-place" changes to the datastructure to produce events which
      will be detected by the unit of work.  See the example at :class:`.HSTORE`
      for a simple example involving a dictionary.
  
      **Support for JSON null vs. SQL NULL**
  
      When working with NULL values, the :class:`.JSON` type recommends the
      use of two specific constants in order to differentiate between a column
      that evaluates to SQL NULL, e.g. no value, vs. the JSON-encoded string
      of ``"null"``.   To insert or select against a value that is SQL NULL,
      use the constant :func:`.null`::
  
          from sqlalchemy import null
          conn.execute(table.insert(), json_value=null())
  
      To insert or select against a value that is JSON ``"null"``, use the
      constant :attr:`.JSON.NULL`::
  
          conn.execute(table.insert(), json_value=JSON.NULL)
  
      The :class:`.JSON` type supports a flag
      :paramref:`.JSON.none_as_null` which when set to True will result
      in the Python constant ``None`` evaluating to the value of SQL
      NULL, and when set to False results in the Python constant
      ``None`` evaluating to the value of JSON ``"null"``.    The Python
      value ``None`` may be used in conjunction with either
      :attr:`.JSON.NULL` and :func:`.null` in order to indicate NULL
      values, but care must be taken as to the value of the
      :paramref:`.JSON.none_as_null` in these cases.
  
      **Customizing the JSON Serializer**
  
      The JSON serializer and deserializer used by :class:`.JSON` defaults to
      Python's ``json.dumps`` and ``json.loads`` functions; in the case of the
      psycopg2 dialect, psycopg2 may be using its own custom loader function.
  
      In order to affect the serializer / deserializer, they are currently
      configurable at the :func:`.create_engine` level via the
      :paramref:`.create_engine.json_serializer` and
      :paramref:`.create_engine.json_deserializer` parameters.  For example,
      to turn off ``ensure_ascii``::
  
          engine = create_engine(
              "sqlite://",
              json_serializer=lambda obj: json.dumps(obj, ensure_ascii=False))
  
      .. versionchanged:: 1.3.7
  
          SQLite dialect's ``json_serializer`` and ``json_deserializer``
          parameters renamed from ``_json_serializer`` and
          ``_json_deserializer``.
  
      .. seealso::
  
          :class:`.postgresql.JSON`
  
          :class:`.postgresql.JSONB`
  
          :class:`.mysql.JSON`
  
          :class:`.sqlite.JSON`
  
      .. versionadded:: 1.1
  
  
      """
  
      __visit_name__ = "JSON"
  
      hashable = False
      NULL = util.symbol("JSON_NULL")
      """Describe the json value of NULL.
  
      This value is used to force the JSON value of ``"null"`` to be
      used as the value.   A value of Python ``None`` will be recognized
      either as SQL NULL or JSON ``"null"``, based on the setting
      of the :paramref:`.JSON.none_as_null` flag; the :attr:`.JSON.NULL`
      constant can be used to always resolve to JSON ``"null"`` regardless
      of this setting.  This is in contrast to the :func:`.sql.null` construct,
      which always resolves to SQL NULL.  E.g.::
  
          from sqlalchemy import null
          from sqlalchemy.dialects.postgresql import JSON
  
          # will *always* insert SQL NULL
          obj1 = MyObject(json_value=null())
  
          # will *always* insert JSON string "null"
          obj2 = MyObject(json_value=JSON.NULL)
  
          session.add_all([obj1, obj2])
          session.commit()
  
      In order to set JSON NULL as a default value for a column, the most
      transparent method is to use :func:`.text`::
  
          Table(
              'my_table', metadata,
              Column('json_data', JSON, default=text("'null'"))
          )
  
      While it is possible to use :attr:`.JSON.NULL` in this context, the
      :attr:`.JSON.NULL` value will be returned as the value of the column,
      which in the context of the ORM or other repurposing of the default
      value, may not be desirable.  Using a SQL expression means the value
      will be re-fetched from the database within the context of retrieving
      generated defaults.
  
  
      """
  
      def __init__(self, none_as_null=False):
          """Construct a :class:`.types.JSON` type.
  
          :param none_as_null=False: if True, persist the value ``None`` as a
           SQL NULL value, not the JSON encoding of ``null``.   Note that
           when this flag is False, the :func:`.null` construct can still
           be used to persist a NULL value::
  
               from sqlalchemy import null
               conn.execute(table.insert(), data=null())
  
           .. note::
  
                :paramref:`.JSON.none_as_null` does **not** apply to the
                values passed to :paramref:`.Column.default` and
                :paramref:`.Column.server_default`; a value of ``None``
                passed for these parameters means "no default present".
  
           .. seealso::
  
                :attr:`.types.JSON.NULL`
  
           """
          self.none_as_null = none_as_null
  
      class JSONElementType(TypeEngine):
          """common function for index / path elements in a JSON expression."""
  
          _integer = Integer()
          _string = String()
  
          def string_bind_processor(self, dialect):
              return self._string._cached_bind_processor(dialect)
  
          def string_literal_processor(self, dialect):
              return self._string._cached_literal_processor(dialect)
  
          def bind_processor(self, dialect):
              int_processor = self._integer._cached_bind_processor(dialect)
              string_processor = self.string_bind_processor(dialect)
  
              def process(value):
                  if int_processor and isinstance(value, int):
                      value = int_processor(value)
                  elif string_processor and isinstance(value, util.string_types):
                      value = string_processor(value)
                  return value
  
              return process
  
          def literal_processor(self, dialect):
              int_processor = self._integer._cached_literal_processor(dialect)
              string_processor = self.string_literal_processor(dialect)
  
              def process(value):
                  if int_processor and isinstance(value, int):
                      value = int_processor(value)
                  elif string_processor and isinstance(value, util.string_types):
                      value = string_processor(value)
                  return value
  
              return process
  
      class JSONIndexType(JSONElementType):
          """Placeholder for the datatype of a JSON index value.
  
          This allows execution-time processing of JSON index values
          for special syntaxes.
  
          """
  
      class JSONPathType(JSONElementType):
          """Placeholder type for JSON path operations.
  
          This allows execution-time processing of a path-based
          index value into a specific SQL syntax.
  
          """
  
      class Comparator(Indexable.Comparator, Concatenable.Comparator):
          """Define comparison operations for :class:`.types.JSON`."""
  
          @util.dependencies("sqlalchemy.sql.default_comparator")
          def _setup_getitem(self, default_comparator, index):
              if not isinstance(index, util.string_types) and isinstance(
                  index, compat.collections_abc.Sequence
              ):
                  index = default_comparator._check_literal(
                      self.expr,
                      operators.json_path_getitem_op,
                      index,
                      bindparam_type=JSON.JSONPathType,
                  )
  
                  operator = operators.json_path_getitem_op
              else:
                  index = default_comparator._check_literal(
                      self.expr,
                      operators.json_getitem_op,
                      index,
                      bindparam_type=JSON.JSONIndexType,
                  )
                  operator = operators.json_getitem_op
  
              return operator, index, self.type
  
          def as_boolean(self):
              """Cast an indexed value as boolean.
  
              e.g.::
  
                  stmt = select([
                      mytable.c.json_column['some_data'].as_boolean()
                  ]).where(
                      mytable.c.json_column['some_data'].as_boolean() == True
                  )
  
              .. versionadded:: 1.3.11
  
              """
              return self._binary_w_type(Boolean(), "as_boolean")
  
          def as_string(self):
              """Cast an indexed value as string.
  
              e.g.::
  
                  stmt = select([
                      mytable.c.json_column['some_data'].as_string()
                  ]).where(
                      mytable.c.json_column['some_data'].as_string() ==
                      'some string'
                  )
  
              .. versionadded:: 1.3.11
  
              """
              return self._binary_w_type(String(), "as_string")
  
          def as_integer(self):
              """Cast an indexed value as integer.
  
              e.g.::
  
                  stmt = select([
                      mytable.c.json_column['some_data'].as_integer()
                  ]).where(
                      mytable.c.json_column['some_data'].as_integer() == 5
                  )
  
              .. versionadded:: 1.3.11
  
              """
              return self._binary_w_type(Integer(), "as_integer")
  
          def as_float(self):
              """Cast an indexed value as float.
  
              e.g.::
  
                  stmt = select([
                      mytable.c.json_column['some_data'].as_float()
                  ]).where(
                      mytable.c.json_column['some_data'].as_float() == 29.75
                  )
  
              .. versionadded:: 1.3.11
  
              """
              # note there's no Numeric or Decimal support here yet
              return self._binary_w_type(Float(), "as_float")
  
          def as_json(self):
              """Cast an indexed value as JSON.
  
              This is the default behavior of indexed elements in any case.
  
              Note that comparison of full JSON structures may not be
              supported by all backends.
  
              .. versionadded:: 1.3.11
  
              """
              return self.expr
  
          def _binary_w_type(self, typ, method_name):
              if not isinstance(
                  self.expr, elements.BinaryExpression
              ) or self.expr.operator not in (
                  operators.json_getitem_op,
                  operators.json_path_getitem_op,
              ):
                  raise exc.InvalidRequestError(
                      "The JSON cast operator JSON.%s() only works with a JSON "
                      "index expression e.g. col['q'].%s()"
                      % (method_name, method_name)
                  )
              expr = self.expr._clone()
              expr.type = typ
              return expr
  
      comparator_factory = Comparator
  
      @property
      def python_type(self):
          return dict
  
      @property
      def should_evaluate_none(self):
          """Alias of :attr:`.JSON.none_as_null`"""
          return not self.none_as_null
  
      @should_evaluate_none.setter
      def should_evaluate_none(self, value):
          self.none_as_null = not value
  
      @util.memoized_property
      def _str_impl(self):
          return String(_expect_unicode=True)
  
      def bind_processor(self, dialect):
          string_process = self._str_impl.bind_processor(dialect)
  
          json_serializer = dialect._json_serializer or json.dumps
  
          def process(value):
              if value is self.NULL:
                  value = None
              elif isinstance(value, elements.Null) or (
                  value is None and self.none_as_null
              ):
                  return None
  
              serialized = json_serializer(value)
              if string_process:
                  serialized = string_process(serialized)
              return serialized
  
          return process
  
      def result_processor(self, dialect, coltype):
          string_process = self._str_impl.result_processor(dialect, coltype)
          json_deserializer = dialect._json_deserializer or json.loads
  
          def process(value):
              if value is None:
                  return None
              if string_process:
                  value = string_process(value)
              return json_deserializer(value)
  
          return process
  
  
  class ARRAY(SchemaEventTarget, Indexable, Concatenable, TypeEngine):
      """Represent a SQL Array type.
  
      .. note::  This type serves as the basis for all ARRAY operations.
         However, currently **only the PostgreSQL backend has support
         for SQL arrays in SQLAlchemy**.  It is recommended to use the
         :class:`.postgresql.ARRAY` type directly when using ARRAY types
         with PostgreSQL, as it provides additional operators specific
         to that backend.
  
      :class:`.types.ARRAY` is part of the Core in support of various SQL
      standard functions such as :class:`.array_agg` which explicitly involve
      arrays; however, with the exception of the PostgreSQL backend and possibly
      some third-party dialects, no other SQLAlchemy built-in dialect has support
      for this type.
  
      An :class:`.types.ARRAY` type is constructed given the "type"
      of element::
  
          mytable = Table("mytable", metadata,
                  Column("data", ARRAY(Integer))
              )
  
      The above type represents an N-dimensional array,
      meaning a supporting backend such as PostgreSQL will interpret values
      with any number of dimensions automatically.   To produce an INSERT
      construct that passes in a 1-dimensional array of integers::
  
          connection.execute(
                  mytable.insert(),
                  data=[1,2,3]
          )
  
      The :class:`.types.ARRAY` type can be constructed given a fixed number
      of dimensions::
  
          mytable = Table("mytable", metadata,
                  Column("data", ARRAY(Integer, dimensions=2))
              )
  
      Sending a number of dimensions is optional, but recommended if the
      datatype is to represent arrays of more than one dimension.  This number
      is used:
  
      * When emitting the type declaration itself to the database, e.g.
        ``INTEGER[][]``
  
      * When translating Python values to database values, and vice versa, e.g.
        an ARRAY of :class:`.Unicode` objects uses this number to efficiently
        access the string values inside of array structures without resorting
        to per-row type inspection
  
      * When used with the Python ``getitem`` accessor, the number of dimensions
        serves to define the kind of type that the ``[]`` operator should
        return, e.g. for an ARRAY of INTEGER with two dimensions::
  
            >>> expr = table.c.column[5]  # returns ARRAY(Integer, dimensions=1)
            >>> expr = expr[6]  # returns Integer
  
      For 1-dimensional arrays, an :class:`.types.ARRAY` instance with no
      dimension parameter will generally assume single-dimensional behaviors.
  
      SQL expressions of type :class:`.types.ARRAY` have support for "index" and
      "slice" behavior.  The Python ``[]`` operator works normally here, given
      integer indexes or slices.  Arrays default to 1-based indexing.
      The operator produces binary expression
      constructs which will produce the appropriate SQL, both for
      SELECT statements::
  
          select([mytable.c.data[5], mytable.c.data[2:7]])
  
      as well as UPDATE statements when the :meth:`.Update.values` method
      is used::
  
          mytable.update().values({
              mytable.c.data[5]: 7,
              mytable.c.data[2:7]: [1, 2, 3]
          })
  
      The :class:`.types.ARRAY` type also provides for the operators
      :meth:`.types.ARRAY.Comparator.any` and
      :meth:`.types.ARRAY.Comparator.all`. The PostgreSQL-specific version of
      :class:`.types.ARRAY` also provides additional operators.
  
      .. versionadded:: 1.1.0
  
      .. seealso::
  
          :class:`.postgresql.ARRAY`
  
      """
  
      __visit_name__ = "ARRAY"
  
      zero_indexes = False
      """if True, Python zero-based indexes should be interpreted as one-based
      on the SQL expression side."""
  
      class Comparator(Indexable.Comparator, Concatenable.Comparator):
  
          """Define comparison operations for :class:`.types.ARRAY`.
  
          More operators are available on the dialect-specific form
          of this type.  See :class:`.postgresql.ARRAY.Comparator`.
  
          """
  
          def _setup_getitem(self, index):
              if isinstance(index, slice):
                  return_type = self.type
                  if self.type.zero_indexes:
                      index = slice(index.start + 1, index.stop + 1, index.step)
                  index = Slice(
                      _literal_as_binds(
                          index.start,
                          name=self.expr.key,
                          type_=type_api.INTEGERTYPE,
                      ),
                      _literal_as_binds(
                          index.stop,
                          name=self.expr.key,
                          type_=type_api.INTEGERTYPE,
                      ),
                      _literal_as_binds(
                          index.step,
                          name=self.expr.key,
                          type_=type_api.INTEGERTYPE,
                      ),
                  )
              else:
                  if self.type.zero_indexes:
                      index += 1
                  if self.type.dimensions is None or self.type.dimensions == 1:
                      return_type = self.type.item_type
                  else:
                      adapt_kw = {"dimensions": self.type.dimensions - 1}
                      return_type = self.type.adapt(
                          self.type.__class__, **adapt_kw
                      )
  
              return operators.getitem, index, return_type
  
          def contains(self, *arg, **kw):
              raise NotImplementedError(
                  "ARRAY.contains() not implemented for the base "
                  "ARRAY type; please use the dialect-specific ARRAY type"
              )
  
          @util.dependencies("sqlalchemy.sql.elements")
          def any(self, elements, other, operator=None):
              """Return ``other operator ANY (array)`` clause.
  
              Argument places are switched, because ANY requires array
              expression to be on the right hand-side.
  
              E.g.::
  
                  from sqlalchemy.sql import operators
  
                  conn.execute(
                      select([table.c.data]).where(
                              table.c.data.any(7, operator=operators.lt)
                          )
                  )
  
              :param other: expression to be compared
              :param operator: an operator object from the
               :mod:`sqlalchemy.sql.operators`
               package, defaults to :func:`.operators.eq`.
  
              .. seealso::
  
                  :func:`.sql.expression.any_`
  
                  :meth:`.types.ARRAY.Comparator.all`
  
              """
              operator = operator if operator else operators.eq
              return operator(
                  elements._literal_as_binds(other),
                  elements.CollectionAggregate._create_any(self.expr),
              )
  
          @util.dependencies("sqlalchemy.sql.elements")
          def all(self, elements, other, operator=None):
              """Return ``other operator ALL (array)`` clause.
  
              Argument places are switched, because ALL requires array
              expression to be on the right hand-side.
  
              E.g.::
  
                  from sqlalchemy.sql import operators
  
                  conn.execute(
                      select([table.c.data]).where(
                              table.c.data.all(7, operator=operators.lt)
                          )
                  )
  
              :param other: expression to be compared
              :param operator: an operator object from the
               :mod:`sqlalchemy.sql.operators`
               package, defaults to :func:`.operators.eq`.
  
              .. seealso::
  
                  :func:`.sql.expression.all_`
  
                  :meth:`.types.ARRAY.Comparator.any`
  
              """
              operator = operator if operator else operators.eq
              return operator(
                  elements._literal_as_binds(other),
                  elements.CollectionAggregate._create_all(self.expr),
              )
  
      comparator_factory = Comparator
  
      def __init__(
          self, item_type, as_tuple=False, dimensions=None, zero_indexes=False
      ):
          """Construct an :class:`.types.ARRAY`.
  
          E.g.::
  
            Column('myarray', ARRAY(Integer))
  
          Arguments are:
  
          :param item_type: The data type of items of this array. Note that
            dimensionality is irrelevant here, so multi-dimensional arrays like
            ``INTEGER[][]``, are constructed as ``ARRAY(Integer)``, not as
            ``ARRAY(ARRAY(Integer))`` or such.
  
          :param as_tuple=False: Specify whether return results
            should be converted to tuples from lists.  This parameter is
            not generally needed as a Python list corresponds well
            to a SQL array.
  
          :param dimensions: if non-None, the ARRAY will assume a fixed
           number of dimensions.   This impacts how the array is declared
           on the database, how it goes about interpreting Python and
           result values, as well as how expression behavior in conjunction
           with the "getitem" operator works.  See the description at
           :class:`.types.ARRAY` for additional detail.
  
          :param zero_indexes=False: when True, index values will be converted
           between Python zero-based and SQL one-based indexes, e.g.
           a value of one will be added to all index values before passing
           to the database.
  
          """
          if isinstance(item_type, ARRAY):
              raise ValueError(
                  "Do not nest ARRAY types; ARRAY(basetype) "
                  "handles multi-dimensional arrays of basetype"
              )
          if isinstance(item_type, type):
              item_type = item_type()
          self.item_type = item_type
          self.as_tuple = as_tuple
          self.dimensions = dimensions
          self.zero_indexes = zero_indexes
  
      @property
      def hashable(self):
          return self.as_tuple
  
      @property
      def python_type(self):
          return list
  
      def compare_values(self, x, y):
          return x == y
  
      def _set_parent(self, column):
          """Support SchemaEventTarget"""
  
          if isinstance(self.item_type, SchemaEventTarget):
              self.item_type._set_parent(column)
  
      def _set_parent_with_dispatch(self, parent):
          """Support SchemaEventTarget"""
  
          super(ARRAY, self)._set_parent_with_dispatch(parent)
  
          if isinstance(self.item_type, SchemaEventTarget):
              self.item_type._set_parent_with_dispatch(parent)
  
  
  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.
  
      :class:`~.types.TIMESTAMP` datatypes have support for timezone
      storage on some backends, such as PostgreSQL and Oracle.  Use the
      :paramref:`~types.TIMESTAMP.timezone` argument in order to enable
      "TIMESTAMP WITH TIMEZONE" for these backends.
  
      """
  
      __visit_name__ = "TIMESTAMP"
  
      def __init__(self, timezone=False):
          """Construct a new :class:`.TIMESTAMP`.
  
          :param timezone: boolean.  Indicates that the TIMESTAMP type should
           enable timezone support, if available on the target database.
           On a per-dialect basis is similar to "TIMESTAMP WITH TIMEZONE".
           If the target database does not support timezones, this flag is
           ignored.
  
  
          """
          super(TIMESTAMP, self).__init__(timezone=timezone)
  
      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"
  
  
  class NullType(TypeEngine):
  
      """An unknown type.
  
      :class:`.NullType` is used as a default type for those cases where
      a type cannot be determined, including:
  
      * During table reflection, when the type of a column is not recognized
        by the :class:`.Dialect`
      * When constructing SQL expressions using plain Python objects of
        unknown types (e.g. ``somecolumn == my_special_object``)
      * When a new :class:`.Column` is created, and the given type is passed
        as ``None`` or is not passed at all.
  
      The :class:`.NullType` can be used within SQL expression invocation
      without issue, it just has no behavior either at the expression
      construction level or at the bind-parameter/result processing level.
      :class:`.NullType` will result in a :exc:`.CompileError` if the compiler
      is asked to render the type itself, such as if it is used in a
      :func:`.cast` operation or within a schema creation operation such as that
      invoked by :meth:`.MetaData.create_all` or the :class:`.CreateTable`
      construct.
  
      """
  
      __visit_name__ = "null"
  
      _isnull = True
  
      hashable = False
  
      def literal_processor(self, dialect):
          def process(value):
              return "NULL"
  
          return process
  
      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
  
  
  class MatchType(Boolean):
      """Refers to the return type of the MATCH operator.
  
      As the :meth:`.ColumnOperators.match` is probably the most open-ended
      operator in generic SQLAlchemy Core, we can't assume the return type
      at SQL evaluation time, as MySQL returns a floating point, not a boolean,
      and other backends might do something different.    So this type
      acts as a placeholder, currently subclassing :class:`.Boolean`.
      The type allows dialects to inject result-processing functionality
      if needed, and on MySQL will return floating-point values.
  
      .. versionadded:: 1.0.0
  
      """
  
  
  NULLTYPE = NullType()
  BOOLEANTYPE = Boolean()
  STRINGTYPE = String()
  INTEGERTYPE = Integer()
  MATCHTYPE = MatchType()
  
  _type_map = {
      int: Integer(),
      float: Float(),
      bool: BOOLEANTYPE,
      decimal.Decimal: Numeric(),
      dt.date: Date(),
      dt.datetime: DateTime(),
      dt.time: Time(),
      dt.timedelta: Interval(),
      util.NoneType: NULLTYPE,
  }
  
  if util.py3k:
      _type_map[bytes] = LargeBinary()  # noqa
      _type_map[str] = Unicode()
  else:
      _type_map[unicode] = Unicode()  # noqa
      _type_map[str] = String()
  
  _type_map_get = _type_map.get
  
  
  def _resolve_value_to_type(value):
      _result_type = _type_map_get(type(value), False)
      if _result_type is False:
          # use inspect() to detect SQLAlchemy built-in
          # objects.
          insp = inspection.inspect(value, False)
          if (
              insp is not None
              and
              # foil mock.Mock() and other impostors by ensuring
              # the inspection target itself self-inspects
              insp.__class__ in inspection._registrars
          ):
              raise exc.ArgumentError(
                  "Object %r is not legal as a SQL literal value" % value
              )
          return NULLTYPE
      else:
          return _result_type
  
  
  # back-assign to type_api
  type_api.BOOLEANTYPE = BOOLEANTYPE
  type_api.STRINGTYPE = STRINGTYPE
  type_api.INTEGERTYPE = INTEGERTYPE
  type_api.NULLTYPE = NULLTYPE
  type_api.MATCHTYPE = MATCHTYPE
  type_api.INDEXABLE = Indexable
  type_api._resolve_value_to_type = _resolve_value_to_type
  TypeEngine.Comparator.BOOLEANTYPE = BOOLEANTYPE
  