s/delay_trait_notifications/hold_trait_notifications/

IPython/config/configurable.py

@@ -1,380 +1,380 b''
 # encoding: utf-8
 """A base class for objects that are configurable."""
 
 # Copyright (c) IPython Development Team.
 # Distributed under the terms of the Modified BSD License.
 
 from __future__ import print_function
 
 import logging
 from copy import deepcopy
 
 from .loader import Config, LazyConfigValue
 from IPython.utils.traitlets import HasTraits, Instance
 from IPython.utils.text import indent, wrap_paragraphs
 from IPython.utils.py3compat import iteritems
 
 
 #-----------------------------------------------------------------------------
 # Helper classes for Configurables
 #-----------------------------------------------------------------------------
 
 
 class ConfigurableError(Exception):
     pass
 
 
 class MultipleInstanceError(ConfigurableError):
     pass
 
 #-----------------------------------------------------------------------------
 # Configurable implementation
 #-----------------------------------------------------------------------------
 
 class Configurable(HasTraits):
 
     config = Instance(Config, (), {})
     parent = Instance('IPython.config.configurable.Configurable')
 
     def __init__(self, **kwargs):
         """Create a configurable given a config config.
 
         Parameters
         ----------
         config : Config
             If this is empty, default values are used. If config is a
             :class:`Config` instance, it will be used to configure the
             instance.
         parent : Configurable instance, optional
             The parent Configurable instance of this object.
 
         Notes
         -----
         Subclasses of Configurable must call the :meth:`__init__` method of
         :class:`Configurable` *before* doing anything else and using
         :func:`super`::
 
             class MyConfigurable(Configurable):
                 def __init__(self, config=None):
                     super(MyConfigurable, self).__init__(config=config)
                     # Then any other code you need to finish initialization.
 
         This ensures that instances will be configured properly.
         """
         parent = kwargs.pop('parent', None)
         if parent is not None:
             # config is implied from parent
             if kwargs.get('config', None) is None:
                 kwargs['config'] = parent.config
             self.parent = parent
         
         config = kwargs.pop('config', None)
         
         # load kwarg traits, other than config
         super(Configurable, self).__init__(**kwargs)
         
         # load config
         if config is not None:
             # We used to deepcopy, but for now we are trying to just save
             # by reference.  This *could* have side effects as all components
             # will share config. In fact, I did find such a side effect in
             # _config_changed below. If a config attribute value was a mutable type
             # all instances of a component were getting the same copy, effectively
             # making that a class attribute.
             # self.config = deepcopy(config)
             self.config = config
         else:
             # allow _config_default to return something
             self._load_config(self.config)
         
         # Ensure explicit kwargs are applied after loading config.
         # This is usually redundant, but ensures config doesn't override
         # explicitly assigned values.
         for key, value in kwargs.items():
             setattr(self, key, value)
 
     #-------------------------------------------------------------------------
     # Static trait notifiations
     #-------------------------------------------------------------------------
     
     @classmethod
     def section_names(cls):
         """return section names as a list"""
         return  [c.__name__ for c in reversed(cls.__mro__) if
             issubclass(c, Configurable) and issubclass(cls, c)
         ]
     
     def _find_my_config(self, cfg):
         """extract my config from a global Config object
         
         will construct a Config object of only the config values that apply to me
         based on my mro(), as well as those of my parent(s) if they exist.
         
         If I am Bar and my parent is Foo, and their parent is Tim,
         this will return merge following config sections, in this order::
         
             [Bar, Foo.bar, Tim.Foo.Bar]
         
         With the last item being the highest priority.
         """
         cfgs = [cfg]
         if self.parent:
             cfgs.append(self.parent._find_my_config(cfg))
         my_config = Config()
         for c in cfgs:
             for sname in self.section_names():
                 # Don't do a blind getattr as that would cause the config to
                 # dynamically create the section with name Class.__name__.
                 if c._has_section(sname):
                     my_config.merge(c[sname])
         return my_config
     
     def _load_config(self, cfg, section_names=None, traits=None):
         """load traits from a Config object"""
         
         if traits is None:
             traits = self.traits(config=True)
         if section_names is None:
             section_names = self.section_names()
         
         my_config = self._find_my_config(cfg)
         
         # hold trait notifications until after all config has been loaded
-        with self.delay_trait_notifications():
+        with self.hold_trait_notifications():
             for name, config_value in iteritems(my_config):
                 if name in traits:
                     if isinstance(config_value, LazyConfigValue):
                         # ConfigValue is a wrapper for using append / update on containers
                         # without having to copy the initial value
                         initial = getattr(self, name)
                         config_value = config_value.get_value(initial)
                     # We have to do a deepcopy here if we don't deepcopy the entire
                     # config object. If we don't, a mutable config_value will be
                     # shared by all instances, effectively making it a class attribute.
                     setattr(self, name, deepcopy(config_value))
 
     def _config_changed(self, name, old, new):
         """Update all the class traits having ``config=True`` as metadata.
 
         For any class trait with a ``config`` metadata attribute that is
         ``True``, we update the trait with the value of the corresponding
         config entry.
         """
         # Get all traits with a config metadata entry that is True
         traits = self.traits(config=True)
 
         # We auto-load config section for this class as well as any parent
         # classes that are Configurable subclasses.  This starts with Configurable
         # and works down the mro loading the config for each section.
         section_names = self.section_names()
         self._load_config(new, traits=traits, section_names=section_names)
 
     def update_config(self, config):
         """Fire the traits events when the config is updated."""
         # Save a copy of the current config.
         newconfig = deepcopy(self.config)
         # Merge the new config into the current one.
         newconfig.merge(config)
         # Save the combined config as self.config, which triggers the traits
         # events.
         self.config = newconfig
 
     @classmethod
     def class_get_help(cls, inst=None):
         """Get the help string for this class in ReST format.
         
         If `inst` is given, it's current trait values will be used in place of
         class defaults.
         """
         assert inst is None or isinstance(inst, cls)
         final_help = []
         final_help.append(u'%s options' % cls.__name__)
         final_help.append(len(final_help[0])*u'-')
         for k, v in sorted(cls.class_traits(config=True).items()):
             help = cls.class_get_trait_help(v, inst)
             final_help.append(help)
         return '\n'.join(final_help)
 
     @classmethod
     def class_get_trait_help(cls, trait, inst=None):
         """Get the help string for a single trait.
         
         If `inst` is given, it's current trait values will be used in place of
         the class default.
         """
         assert inst is None or isinstance(inst, cls)
         lines = []
         header = "--%s.%s=<%s>" % (cls.__name__, trait.name, trait.__class__.__name__)
         lines.append(header)
         if inst is not None:
             lines.append(indent('Current: %r' % getattr(inst, trait.name), 4))
         else:
             try:
                 dvr = repr(trait.get_default_value())
             except Exception:
                 dvr = None # ignore defaults we can't construct
             if dvr is not None:
                 if len(dvr) > 64:
                     dvr = dvr[:61]+'...'
                 lines.append(indent('Default: %s' % dvr, 4))
         if 'Enum' in trait.__class__.__name__:
             # include Enum choices
             lines.append(indent('Choices: %r' % (trait.values,)))
 
         help = trait.get_metadata('help')
         if help is not None:
             help = '\n'.join(wrap_paragraphs(help, 76))
             lines.append(indent(help, 4))
         return '\n'.join(lines)
 
     @classmethod
     def class_print_help(cls, inst=None):
         """Get the help string for a single trait and print it."""
         print(cls.class_get_help(inst))
 
     @classmethod
     def class_config_section(cls):
         """Get the config class config section"""
         def c(s):
             """return a commented, wrapped block."""
             s = '\n\n'.join(wrap_paragraphs(s, 78))
 
             return '# ' + s.replace('\n', '\n# ')
 
         # section header
         breaker = '#' + '-'*78
         s = "# %s configuration" % cls.__name__
         lines = [breaker, s, breaker, '']
         # get the description trait
         desc = cls.class_traits().get('description')
         if desc:
             desc = desc.default_value
         else:
             # no description trait, use __doc__
             desc = getattr(cls, '__doc__', '')
         if desc:
             lines.append(c(desc))
             lines.append('')
 
         parents = []
         for parent in cls.mro():
             # only include parents that are not base classes
             # and are not the class itself
             # and have some configurable traits to inherit
             if parent is not cls and issubclass(parent, Configurable) and \
                     parent.class_traits(config=True):
                 parents.append(parent)
 
         if parents:
             pstr = ', '.join([ p.__name__ for p in parents ])
             lines.append(c('%s will inherit config from: %s'%(cls.__name__, pstr)))
             lines.append('')
 
         for name, trait in iteritems(cls.class_traits(config=True)):
             help = trait.get_metadata('help') or ''
             lines.append(c(help))
             lines.append('# c.%s.%s = %r'%(cls.__name__, name, trait.get_default_value()))
             lines.append('')
         return '\n'.join(lines)
 
 
 
 class SingletonConfigurable(Configurable):
     """A configurable that only allows one instance.
 
     This class is for classes that should only have one instance of itself
     or *any* subclass. To create and retrieve such a class use the
     :meth:`SingletonConfigurable.instance` method.
     """
 
     _instance = None
 
     @classmethod
     def _walk_mro(cls):
         """Walk the cls.mro() for parent classes that are also singletons
 
         For use in instance()
         """
 
         for subclass in cls.mro():
             if issubclass(cls, subclass) and \
                     issubclass(subclass, SingletonConfigurable) and \
                     subclass != SingletonConfigurable:
                 yield subclass
 
     @classmethod
     def clear_instance(cls):
         """unset _instance for this class and singleton parents.
         """
         if not cls.initialized():
             return
         for subclass in cls._walk_mro():
             if isinstance(subclass._instance, cls):
                 # only clear instances that are instances
                 # of the calling class
                 subclass._instance = None
 
     @classmethod
     def instance(cls, *args, **kwargs):
         """Returns a global instance of this class.
 
         This method create a new instance if none have previously been created
         and returns a previously created instance is one already exists.
 
         The arguments and keyword arguments passed to this method are passed
         on to the :meth:`__init__` method of the class upon instantiation.
 
         Examples
         --------
 
         Create a singleton class using instance, and retrieve it::
 
             >>> from IPython.config.configurable import SingletonConfigurable
             >>> class Foo(SingletonConfigurable): pass
             >>> foo = Foo.instance()
             >>> foo == Foo.instance()
             True
 
         Create a subclass that is retrived using the base class instance::
 
             >>> class Bar(SingletonConfigurable): pass
             >>> class Bam(Bar): pass
             >>> bam = Bam.instance()
             >>> bam == Bar.instance()
             True
         """
         # Create and save the instance
         if cls._instance is None:
             inst = cls(*args, **kwargs)
             # Now make sure that the instance will also be returned by
             # parent classes' _instance attribute.
             for subclass in cls._walk_mro():
                 subclass._instance = inst
 
         if isinstance(cls._instance, cls):
             return cls._instance
         else:
             raise MultipleInstanceError(
                 'Multiple incompatible subclass instances of '
                 '%s are being created.' % cls.__name__
             )
 
     @classmethod
     def initialized(cls):
         """Has an instance been created?"""
         return hasattr(cls, "_instance") and cls._instance is not None
 
 
 class LoggingConfigurable(Configurable):
     """A parent class for Configurables that log.
 
     Subclasses have a log trait, and the default behavior
     is to get the logger from the currently running Application.
     """
 
     log = Instance('logging.Logger')
     def _log_default(self):
         from IPython.utils import log
         return log.get_logger()
 
 

IPython/utils/traitlets.py

@@ -1,1831 +1,1831 b''
 # encoding: utf-8
 """
 A lightweight Traits like module.
 
 This is designed to provide a lightweight, simple, pure Python version of
 many of the capabilities of enthought.traits.  This includes:
 
 * Validation
 * Type specification with defaults
 * Static and dynamic notification
 * Basic predefined types
 * An API that is similar to enthought.traits
 
 We don't support:
 
 * Delegation
 * Automatic GUI generation
 * A full set of trait types.  Most importantly, we don't provide container
   traits (list, dict, tuple) that can trigger notifications if their
   contents change.
 * API compatibility with enthought.traits
 
 There are also some important difference in our design:
 
 * enthought.traits does not validate default values.  We do.
 
 We choose to create this module because we need these capabilities, but
 we need them to be pure Python so they work in all Python implementations,
 including Jython and IronPython.
 
 Inheritance diagram:
 
 .. inheritance-diagram:: IPython.utils.traitlets
    :parts: 3
 """
 
 # Copyright (c) IPython Development Team.
 # Distributed under the terms of the Modified BSD License.
 #
 # Adapted from enthought.traits, Copyright (c) Enthought, Inc.,
 # also under the terms of the Modified BSD License.
 
 import contextlib
 import inspect
 import re
 import sys
 import types
 from types import FunctionType
 try:
     from types import ClassType, InstanceType
     ClassTypes = (ClassType, type)
 except:
     ClassTypes = (type,)
 from warnings import warn
 
 from .importstring import import_item
 from IPython.utils import py3compat
 from IPython.utils import eventful
 from IPython.utils.py3compat import iteritems, string_types
 from IPython.testing.skipdoctest import skip_doctest
 
 SequenceTypes = (list, tuple, set, frozenset)
 
 #-----------------------------------------------------------------------------
 # Basic classes
 #-----------------------------------------------------------------------------
 
 
 class NoDefaultSpecified ( object ): pass
 NoDefaultSpecified = NoDefaultSpecified()
 
 
 class Undefined ( object ): pass
 Undefined = Undefined()
 
 class TraitError(Exception):
     pass
 
 #-----------------------------------------------------------------------------
 # Utilities
 #-----------------------------------------------------------------------------
 
 
 def class_of ( object ):
     """ Returns a string containing the class name of an object with the
     correct indefinite article ('a' or 'an') preceding it (e.g., 'an Image',
     'a PlotValue').
     """
     if isinstance( object, py3compat.string_types ):
         return add_article( object )
 
     return add_article( object.__class__.__name__ )
 
 
 def add_article ( name ):
     """ Returns a string containing the correct indefinite article ('a' or 'an')
     prefixed to the specified string.
     """
     if name[:1].lower() in 'aeiou':
        return 'an ' + name
 
     return 'a ' + name
 
 
 def repr_type(obj):
     """ Return a string representation of a value and its type for readable
     error messages.
     """
     the_type = type(obj)
     if (not py3compat.PY3) and the_type is InstanceType:
         # Old-style class.
         the_type = obj.__class__
     msg = '%r %r' % (obj, the_type)
     return msg
 
 
 def is_trait(t):
     """ Returns whether the given value is an instance or subclass of TraitType.
     """
     return (isinstance(t, TraitType) or
             (isinstance(t, type) and issubclass(t, TraitType)))
 
 
 def parse_notifier_name(name):
     """Convert the name argument to a list of names.
 
     Examples
     --------
 
     >>> parse_notifier_name('a')
     ['a']
     >>> parse_notifier_name(['a','b'])
     ['a', 'b']
     >>> parse_notifier_name(None)
     ['anytrait']
     """
     if isinstance(name, string_types):
         return [name]
     elif name is None:
         return ['anytrait']
     elif isinstance(name, (list, tuple)):
         for n in name:
             assert isinstance(n, string_types), "names must be strings"
         return name
 
 
 class _SimpleTest:
     def __init__ ( self, value ): self.value = value
     def __call__ ( self, test  ):
         return test == self.value
     def __repr__(self):
         return "<SimpleTest(%r)" % self.value
     def __str__(self):
         return self.__repr__()
 
 
 def getmembers(object, predicate=None):
     """A safe version of inspect.getmembers that handles missing attributes.
 
     This is useful when there are descriptor based attributes that for
     some reason raise AttributeError even though they exist.  This happens
     in zope.inteface with the __provides__ attribute.
     """
     results = []
     for key in dir(object):
         try:
             value = getattr(object, key)
         except AttributeError:
             pass
         else:
             if not predicate or predicate(value):
                 results.append((key, value))
     results.sort()
     return results
 
 def _validate_link(*tuples):
     """Validate arguments for traitlet link functions"""
     for t in tuples:
         if not len(t) == 2:
             raise TypeError("Each linked traitlet must be specified as (HasTraits, 'trait_name'), not %r" % t)
         obj, trait_name = t
         if not isinstance(obj, HasTraits):
             raise TypeError("Each object must be HasTraits, not %r" % type(obj))
         if not trait_name in obj.traits():
             raise TypeError("%r has no trait %r" % (obj, trait_name))
 
 @skip_doctest
 class link(object):
     """Link traits from different objects together so they remain in sync.
 
     Parameters
     ----------
     *args : pairs of objects/attributes
 
     Examples
     --------
 
     >>> c = link((obj1, 'value'), (obj2, 'value'), (obj3, 'value'))
     >>> obj1.value = 5 # updates other objects as well
     """
     updating = False
     def __init__(self, *args):
         if len(args) < 2:
             raise TypeError('At least two traitlets must be provided.')
         _validate_link(*args)
 
         self.objects = {}
 
         initial = getattr(args[0][0], args[0][1])
         for obj, attr in args:
             setattr(obj, attr, initial)
 
             callback = self._make_closure(obj, attr)
             obj.on_trait_change(callback, attr)
             self.objects[(obj, attr)] = callback
 
     @contextlib.contextmanager
     def _busy_updating(self):
         self.updating = True
         try:
             yield
         finally:
             self.updating = False
 
     def _make_closure(self, sending_obj, sending_attr):
         def update(name, old, new):
             self._update(sending_obj, sending_attr, new)
         return update
 
     def _update(self, sending_obj, sending_attr, new):
         if self.updating:
             return
         with self._busy_updating():
             for obj, attr in self.objects.keys():
                 setattr(obj, attr, new)
 
     def unlink(self):
         for key, callback in self.objects.items():
             (obj, attr) = key
             obj.on_trait_change(callback, attr, remove=True)
 
 @skip_doctest
 class directional_link(object):
     """Link the trait of a source object with traits of target objects.
 
     Parameters
     ----------
     source : pair of object, name
     targets : pairs of objects/attributes
 
     Examples
     --------
 
     >>> c = directional_link((src, 'value'), (tgt1, 'value'), (tgt2, 'value'))
     >>> src.value = 5  # updates target objects
     >>> tgt1.value = 6 # does not update other objects
     """
     updating = False
 
     def __init__(self, source, *targets):
         if len(targets) < 1:
             raise TypeError('At least two traitlets must be provided.')
         _validate_link(source, *targets)
         self.source = source
         self.targets = targets
 
         # Update current value
         src_attr_value = getattr(source[0], source[1])
         for obj, attr in targets:
             setattr(obj, attr, src_attr_value)
 
         # Wire
         self.source[0].on_trait_change(self._update, self.source[1])
 
     @contextlib.contextmanager
     def _busy_updating(self):
         self.updating = True
         try:
             yield
         finally:
             self.updating = False
 
     def _update(self, name, old, new):
         if self.updating:
             return
         with self._busy_updating():
             for obj, attr in self.targets:
                 setattr(obj, attr, new)
 
     def unlink(self):
         self.source[0].on_trait_change(self._update, self.source[1], remove=True)
         self.source = None
         self.targets = []
 
 dlink = directional_link
 
 #-----------------------------------------------------------------------------
 # Base TraitType for all traits
 #-----------------------------------------------------------------------------
 
 
 class TraitType(object):
     """A base class for all trait descriptors.
 
     Notes
     -----
     Our implementation of traits is based on Python's descriptor
     prototol.  This class is the base class for all such descriptors.  The
     only magic we use is a custom metaclass for the main :class:`HasTraits`
     class that does the following:
 
     1. Sets the :attr:`name` attribute of every :class:`TraitType`
        instance in the class dict to the name of the attribute.
     2. Sets the :attr:`this_class` attribute of every :class:`TraitType`
        instance in the class dict to the *class* that declared the trait.
        This is used by the :class:`This` trait to allow subclasses to
        accept superclasses for :class:`This` values.
     """
 
 
     metadata = {}
     default_value = Undefined
     allow_none = False
     info_text = 'any value'
 
     def __init__(self, default_value=NoDefaultSpecified, allow_none=None, **metadata):
         """Create a TraitType.
         """
         if default_value is not NoDefaultSpecified:
             self.default_value = default_value
         if allow_none is not None:
             self.allow_none = allow_none
 
         if 'default' in metadata:
             # Warn the user that they probably meant default_value.
             warn(
                 "Parameter 'default' passed to TraitType. "
                 "Did you mean 'default_value'?"
             )
 
         if len(metadata) > 0:
             if len(self.metadata) > 0:
                 self._metadata = self.metadata.copy()
                 self._metadata.update(metadata)
             else:
                 self._metadata = metadata
         else:
             self._metadata = self.metadata
 
         self.init()
 
     def init(self):
         pass
 
     def get_default_value(self):
         """Create a new instance of the default value."""
         return self.default_value
 
     def instance_init(self):
         """Part of the initialization which may depends on the underlying
         HasTraits instance.
 
         It is typically overloaded for specific trait types.
 
         This method is called by :meth:`HasTraits.__new__` and in the
         :meth:`TraitType.instance_init` method of trait types holding
         other trait types.
         """
         pass
 
     def init_default_value(self, obj):
         """Instantiate the default value for the trait type.
 
         This method is called by :meth:`TraitType.set_default_value` in the
         case a default value is provided at construction time or later when
         accessing the trait value for the first time in
         :meth:`HasTraits.__get__`.
         """
         value = self.get_default_value()
         value = self._validate(obj, value)
         obj._trait_values[self.name] = value
         return value
 
     def set_default_value(self, obj):
         """Set the default value on a per instance basis.
 
         This method is called by :meth:`HasTraits.__new__` to instantiate and
         validate the default value. The creation and validation of
         default values must be delayed until the parent :class:`HasTraits`
         class has been instantiated.
         Parameters
         ----------
         obj : :class:`HasTraits` instance
             The parent :class:`HasTraits` instance that has just been
             created.
         """
         # Check for a deferred initializer defined in the same class as the
         # trait declaration or above.
         mro = type(obj).mro()
         meth_name = '_%s_default' % self.name
         for cls in mro[:mro.index(self.this_class)+1]:
             if meth_name in cls.__dict__:
                 break
         else:
             # We didn't find one. Do static initialization.
             self.init_default_value(obj)
             return
         # Complete the dynamic initialization.
         obj._trait_dyn_inits[self.name] = meth_name
 
     def __get__(self, obj, cls=None):
         """Get the value of the trait by self.name for the instance.
 
         Default values are instantiated when :meth:`HasTraits.__new__`
         is called.  Thus by the time this method gets called either the
         default value or a user defined value (they called :meth:`__set__`)
         is in the :class:`HasTraits` instance.
         """
         if obj is None:
             return self
         else:
             try:
                 value = obj._trait_values[self.name]
             except KeyError:
                 # Check for a dynamic initializer.
                 if self.name in obj._trait_dyn_inits:
                     method = getattr(obj, obj._trait_dyn_inits[self.name])
                     value = method()
                     # FIXME: Do we really validate here?
                     value = self._validate(obj, value)
                     obj._trait_values[self.name] = value
                     return value
                 else:
                     return self.init_default_value(obj)
             except Exception:
                 # HasTraits should call set_default_value to populate
                 # this.  So this should never be reached.
                 raise TraitError('Unexpected error in TraitType: '
                                  'default value not set properly')
             else:
                 return value
 
     def __set__(self, obj, value):
         new_value = self._validate(obj, value)
         try:
             old_value = obj._trait_values[self.name]
         except KeyError:
             old_value = None
 
         obj._trait_values[self.name] = new_value
         try:
             silent = bool(old_value == new_value)
         except:
             # if there is an error in comparing, default to notify
             silent = False
         if silent is not True:
             # we explicitly compare silent to True just in case the equality
             # comparison above returns something other than True/False
             obj._notify_trait(self.name, old_value, new_value)
 
     def _validate(self, obj, value):
         if value is None and self.allow_none:
             return value
         if hasattr(self, 'validate'):
             value = self.validate(obj, value)
         try:
             obj_validate = getattr(obj, '_%s_validate' % self.name)
         except (AttributeError, RuntimeError):
             # Qt mixins raise RuntimeError on missing attrs accessed before __init__
             pass
         else:
             value = obj_validate(value, self)
         return value
 
     def __or__(self, other):
         if isinstance(other, Union):
             return Union([self] + other.trait_types)
         else:
             return Union([self, other])
 
     def info(self):
         return self.info_text
 
     def error(self, obj, value):
         if obj is not None:
             e = "The '%s' trait of %s instance must be %s, but a value of %s was specified." \
                 % (self.name, class_of(obj),
                    self.info(), repr_type(value))
         else:
             e = "The '%s' trait must be %s, but a value of %r was specified." \
                 % (self.name, self.info(), repr_type(value))
         raise TraitError(e)
 
     def get_metadata(self, key, default=None):
         return getattr(self, '_metadata', {}).get(key, default)
 
     def set_metadata(self, key, value):
         getattr(self, '_metadata', {})[key] = value
 
 
 #-----------------------------------------------------------------------------
 # The HasTraits implementation
 #-----------------------------------------------------------------------------
 
 
 class MetaHasTraits(type):
     """A metaclass for HasTraits.
 
     This metaclass makes sure that any TraitType class attributes are
     instantiated and sets their name attribute.
     """
 
     def __new__(mcls, name, bases, classdict):
         """Create the HasTraits class.
 
         This instantiates all TraitTypes in the class dict and sets their
         :attr:`name` attribute.
         """
         # print "MetaHasTraitlets (mcls, name): ", mcls, name
         # print "MetaHasTraitlets (bases): ", bases
         # print "MetaHasTraitlets (classdict): ", classdict
         for k,v in iteritems(classdict):
             if isinstance(v, TraitType):
                 v.name = k
             elif inspect.isclass(v):
                 if issubclass(v, TraitType):
                     vinst = v()
                     vinst.name = k
                     classdict[k] = vinst
         return super(MetaHasTraits, mcls).__new__(mcls, name, bases, classdict)
 
     def __init__(cls, name, bases, classdict):
         """Finish initializing the HasTraits class.
 
         This sets the :attr:`this_class` attribute of each TraitType in the
         class dict to the newly created class ``cls``.
         """
         for k, v in iteritems(classdict):
             if isinstance(v, TraitType):
                 v.this_class = cls
         super(MetaHasTraits, cls).__init__(name, bases, classdict)
 
 class HasTraits(py3compat.with_metaclass(MetaHasTraits, object)):
 
     def __new__(cls, *args, **kw):
         # This is needed because object.__new__ only accepts
         # the cls argument.
         new_meth = super(HasTraits, cls).__new__
         if new_meth is object.__new__:
             inst = new_meth(cls)
         else:
             inst = new_meth(cls, **kw)
         inst._trait_values = {}
         inst._trait_notifiers = {}
         inst._trait_dyn_inits = {}
         # Here we tell all the TraitType instances to set their default
         # values on the instance.
         for key in dir(cls):
             # Some descriptors raise AttributeError like zope.interface's
             # __provides__ attributes even though they exist.  This causes
             # AttributeErrors even though they are listed in dir(cls).
             try:
                 value = getattr(cls, key)
             except AttributeError:
                 pass
             else:
                 if isinstance(value, TraitType):
                     value.instance_init()
                     if key not in kw:
                         value.set_default_value(inst)
 
         return inst
 
     def __init__(self, *args, **kw):
         # Allow trait values to be set using keyword arguments.
         # We need to use setattr for this to trigger validation and
         # notifications.
         
-        with self.delay_trait_notifications():
+        with self.hold_trait_notifications():
             for key, value in iteritems(kw):
                 setattr(self, key, value)
     
     @contextlib.contextmanager
-    def delay_trait_notifications(self):
+    def hold_trait_notifications(self):
         """Context manager for bundling trait change notifications
         
         Use this when doing multiple trait assignments (init, config),
         to avoid race conditions in trait notifiers requesting other trait values.
         All trait notifications will fire after all values have been assigned.
         """
         _notify_trait = self._notify_trait
         notifications = []
         self._notify_trait = lambda *a: notifications.append(a)
         
         try:
             yield
         finally:
             self._notify_trait = _notify_trait
             if isinstance(_notify_trait, types.MethodType):
                 # FIXME: remove when support is bumped to 3.4.
                 # when original method is restored,
                 # remove the redundant value from __dict__
                 # (only used to preserve pickleability on Python < 3.4)
                 self.__dict__.pop('_notify_trait', None)
         # trigger delayed notifications
         for args in notifications:
             self._notify_trait(*args)
 
     def _notify_trait(self, name, old_value, new_value):
 
         # First dynamic ones
         callables = []
         callables.extend(self._trait_notifiers.get(name,[]))
         callables.extend(self._trait_notifiers.get('anytrait',[]))
 
         # Now static ones
         try:
             cb = getattr(self, '_%s_changed' % name)
         except:
             pass
         else:
             callables.append(cb)
 
         # Call them all now
         for c in callables:
             # Traits catches and logs errors here.  I allow them to raise
             if callable(c):
                 argspec = inspect.getargspec(c)
                 nargs = len(argspec[0])
                 # Bound methods have an additional 'self' argument
                 # I don't know how to treat unbound methods, but they
                 # can't really be used for callbacks.
                 if isinstance(c, types.MethodType):
                     offset = -1
                 else:
                     offset = 0
                 if nargs + offset == 0:
                     c()
                 elif nargs + offset == 1:
                     c(name)
                 elif nargs + offset == 2:
                     c(name, new_value)
                 elif nargs + offset == 3:
                     c(name, old_value, new_value)
                 else:
                     raise TraitError('a trait changed callback '
                                         'must have 0-3 arguments.')
             else:
                 raise TraitError('a trait changed callback '
                                     'must be callable.')
 
 
     def _add_notifiers(self, handler, name):
         if name not in self._trait_notifiers:
             nlist = []
             self._trait_notifiers[name] = nlist
         else:
             nlist = self._trait_notifiers[name]
         if handler not in nlist:
             nlist.append(handler)
 
     def _remove_notifiers(self, handler, name):
         if name in self._trait_notifiers:
             nlist = self._trait_notifiers[name]
             try:
                 index = nlist.index(handler)
             except ValueError:
                 pass
             else:
                 del nlist[index]
 
     def on_trait_change(self, handler, name=None, remove=False):
         """Setup a handler to be called when a trait changes.
 
         This is used to setup dynamic notifications of trait changes.
 
         Static handlers can be created by creating methods on a HasTraits
         subclass with the naming convention '_[traitname]_changed'.  Thus,
         to create static handler for the trait 'a', create the method
         _a_changed(self, name, old, new) (fewer arguments can be used, see
         below).
 
         Parameters
         ----------
         handler : callable
             A callable that is called when a trait changes.  Its
             signature can be handler(), handler(name), handler(name, new)
             or handler(name, old, new).
         name : list, str, None
             If None, the handler will apply to all traits.  If a list
             of str, handler will apply to all names in the list.  If a
             str, the handler will apply just to that name.
         remove : bool
             If False (the default), then install the handler.  If True
             then unintall it.
         """
         if remove:
             names = parse_notifier_name(name)
             for n in names:
                 self._remove_notifiers(handler, n)
         else:
             names = parse_notifier_name(name)
             for n in names:
                 self._add_notifiers(handler, n)
 
     @classmethod
     def class_trait_names(cls, **metadata):
         """Get a list of all the names of this class' traits.
 
         This method is just like the :meth:`trait_names` method,
         but is unbound.
         """
         return cls.class_traits(**metadata).keys()
 
     @classmethod
     def class_traits(cls, **metadata):
         """Get a `dict` of all the traits of this class.  The dictionary
         is keyed on the name and the values are the TraitType objects.
 
         This method is just like the :meth:`traits` method, but is unbound.
 
         The TraitTypes returned don't know anything about the values
         that the various HasTrait's instances are holding.
 
         The metadata kwargs allow functions to be passed in which
         filter traits based on metadata values.  The functions should
         take a single value as an argument and return a boolean.  If
         any function returns False, then the trait is not included in
         the output.  This does not allow for any simple way of
         testing that a metadata name exists and has any
         value because get_metadata returns None if a metadata key
         doesn't exist.
         """
         traits = dict([memb for memb in getmembers(cls) if
                      isinstance(memb[1], TraitType)])
 
         if len(metadata) == 0:
             return traits
 
         for meta_name, meta_eval in metadata.items():
             if type(meta_eval) is not FunctionType:
                 metadata[meta_name] = _SimpleTest(meta_eval)
 
         result = {}
         for name, trait in traits.items():
             for meta_name, meta_eval in metadata.items():
                 if not meta_eval(trait.get_metadata(meta_name)):
                     break
             else:
                 result[name] = trait
 
         return result
 
     def trait_names(self, **metadata):
         """Get a list of all the names of this class' traits."""
         return self.traits(**metadata).keys()
 
     def traits(self, **metadata):
         """Get a `dict` of all the traits of this class.  The dictionary
         is keyed on the name and the values are the TraitType objects.
 
         The TraitTypes returned don't know anything about the values
         that the various HasTrait's instances are holding.
 
         The metadata kwargs allow functions to be passed in which
         filter traits based on metadata values.  The functions should
         take a single value as an argument and return a boolean.  If
         any function returns False, then the trait is not included in
         the output.  This does not allow for any simple way of
         testing that a metadata name exists and has any
         value because get_metadata returns None if a metadata key
         doesn't exist.
         """
         traits = dict([memb for memb in getmembers(self.__class__) if
                      isinstance(memb[1], TraitType)])
 
         if len(metadata) == 0:
             return traits
 
         for meta_name, meta_eval in metadata.items():
             if type(meta_eval) is not FunctionType:
                 metadata[meta_name] = _SimpleTest(meta_eval)
 
         result = {}
         for name, trait in traits.items():
             for meta_name, meta_eval in metadata.items():
                 if not meta_eval(trait.get_metadata(meta_name)):
                     break
             else:
                 result[name] = trait
 
         return result
 
     def trait_metadata(self, traitname, key, default=None):
         """Get metadata values for trait by key."""
         try:
             trait = getattr(self.__class__, traitname)
         except AttributeError:
             raise TraitError("Class %s does not have a trait named %s" %
                                 (self.__class__.__name__, traitname))
         else:
             return trait.get_metadata(key, default)
 
 #-----------------------------------------------------------------------------
 # Actual TraitTypes implementations/subclasses
 #-----------------------------------------------------------------------------
 
 #-----------------------------------------------------------------------------
 # TraitTypes subclasses for handling classes and instances of classes
 #-----------------------------------------------------------------------------
 
 
 class ClassBasedTraitType(TraitType):
     """
     A trait with error reporting and string -> type resolution for Type,
     Instance and This.
     """
 
     def _resolve_string(self, string):
         """
         Resolve a string supplied for a type into an actual object.
         """
         return import_item(string)
 
     def error(self, obj, value):
         kind = type(value)
         if (not py3compat.PY3) and kind is InstanceType:
             msg = 'class %s' % value.__class__.__name__
         else:
             msg = '%s (i.e. %s)' % ( str( kind )[1:-1], repr( value ) )
 
         if obj is not None:
             e = "The '%s' trait of %s instance must be %s, but a value of %s was specified." \
                 % (self.name, class_of(obj),
                    self.info(), msg)
         else:
             e = "The '%s' trait must be %s, but a value of %r was specified." \
                 % (self.name, self.info(), msg)
 
         raise TraitError(e)
 
 
 class Type(ClassBasedTraitType):
     """A trait whose value must be a subclass of a specified class."""
 
     def __init__ (self, default_value=None, klass=None, allow_none=True, **metadata ):
         """Construct a Type trait
 
         A Type trait specifies that its values must be subclasses of
         a particular class.
 
         If only ``default_value`` is given, it is used for the ``klass`` as
         well.
 
         Parameters
         ----------
         default_value : class, str or None
             The default value must be a subclass of klass.  If an str,
             the str must be a fully specified class name, like 'foo.bar.Bah'.
             The string is resolved into real class, when the parent
             :class:`HasTraits` class is instantiated.
         klass : class, str, None
             Values of this trait must be a subclass of klass.  The klass
             may be specified in a string like: 'foo.bar.MyClass'.
             The string is resolved into real class, when the parent
             :class:`HasTraits` class is instantiated.
         allow_none : bool [ default True ]
             Indicates whether None is allowed as an assignable value. Even if
             ``False``, the default value may be ``None``.
         """
         if default_value is None:
             if klass is None:
                 klass = object
         elif klass is None:
             klass = default_value
 
         if not (inspect.isclass(klass) or isinstance(klass, py3compat.string_types)):
             raise TraitError("A Type trait must specify a class.")
 
         self.klass       = klass
 
         super(Type, self).__init__(default_value, allow_none=allow_none, **metadata)
 
     def validate(self, obj, value):
         """Validates that the value is a valid object instance."""
         if isinstance(value, py3compat.string_types):
             try:
                 value = self._resolve_string(value)
             except ImportError:
                 raise TraitError("The '%s' trait of %s instance must be a type, but "
                                  "%r could not be imported" % (self.name, obj, value))
         try:
             if issubclass(value, self.klass):
                 return value
         except:
             pass
 
         self.error(obj, value)
 
     def info(self):
         """ Returns a description of the trait."""
         if isinstance(self.klass, py3compat.string_types):
             klass = self.klass
         else:
             klass = self.klass.__name__
         result = 'a subclass of ' + klass
         if self.allow_none:
             return result + ' or None'
         return result
 
     def instance_init(self):
         self._resolve_classes()
         super(Type, self).instance_init()
 
     def _resolve_classes(self):
         if isinstance(self.klass, py3compat.string_types):
             self.klass = self._resolve_string(self.klass)
         if isinstance(self.default_value, py3compat.string_types):
             self.default_value = self._resolve_string(self.default_value)
 
     def get_default_value(self):
         return self.default_value
 
 
 class DefaultValueGenerator(object):
     """A class for generating new default value instances."""
 
     def __init__(self, *args, **kw):
         self.args = args
         self.kw = kw
 
     def generate(self, klass):
         return klass(*self.args, **self.kw)
 
 
 class Instance(ClassBasedTraitType):
     """A trait whose value must be an instance of a specified class.
 
     The value can also be an instance of a subclass of the specified class.
 
     Subclasses can declare default classes by overriding the klass attribute
     """
 
     klass = None
 
     def __init__(self, klass=None, args=None, kw=None,
                  allow_none=True, **metadata ):
         """Construct an Instance trait.
 
         This trait allows values that are instances of a particular
         class or its subclasses.  Our implementation is quite different
         from that of enthough.traits as we don't allow instances to be used
         for klass and we handle the ``args`` and ``kw`` arguments differently.
 
         Parameters
         ----------
         klass : class, str
             The class that forms the basis for the trait.  Class names
             can also be specified as strings, like 'foo.bar.Bar'.
         args : tuple
             Positional arguments for generating the default value.
         kw : dict
             Keyword arguments for generating the default value.
         allow_none : bool [default True]
             Indicates whether None is allowed as a value.
 
         Notes
         -----
         If both ``args`` and ``kw`` are None, then the default value is None.
         If ``args`` is a tuple and ``kw`` is a dict, then the default is
         created as ``klass(*args, **kw)``.  If exactly one of ``args`` or ``kw`` is
         None, the None is replaced by ``()`` or ``{}``, respectively.
         """
         if klass is None:
             klass = self.klass
         
         if (klass is not None) and (inspect.isclass(klass) or isinstance(klass, py3compat.string_types)):
             self.klass = klass
         else:
             raise TraitError('The klass attribute must be a class'
                                 ' not: %r' % klass)
 
         # self.klass is a class, so handle default_value
         if args is None and kw is None:
             default_value = None
         else:
             if args is None:
                 # kw is not None
                 args = ()
             elif kw is None:
                 # args is not None
                 kw = {}
 
             if not isinstance(kw, dict):
                 raise TraitError("The 'kw' argument must be a dict or None.")
             if not isinstance(args, tuple):
                 raise TraitError("The 'args' argument must be a tuple or None.")
 
             default_value = DefaultValueGenerator(*args, **kw)
 
         super(Instance, self).__init__(default_value, allow_none=allow_none, **metadata)
 
     def validate(self, obj, value):
         if isinstance(value, self.klass):
             return value
         else:
             self.error(obj, value)
 
     def info(self):
         if isinstance(self.klass, py3compat.string_types):
             klass = self.klass
         else:
             klass = self.klass.__name__
         result = class_of(klass)
         if self.allow_none:
             return result + ' or None'
 
         return result
 
     def instance_init(self):
         self._resolve_classes()
         super(Instance, self).instance_init()
 
     def _resolve_classes(self):
         if isinstance(self.klass, py3compat.string_types):
             self.klass = self._resolve_string(self.klass)
 
     def get_default_value(self):
         """Instantiate a default value instance.
 
         This is called when the containing HasTraits classes'
         :meth:`__new__` method is called to ensure that a unique instance
         is created for each HasTraits instance.
         """
         dv  = self.default_value
         if isinstance(dv, DefaultValueGenerator):
             return dv.generate(self.klass)
         else:
             return dv
 
 
 class ForwardDeclaredMixin(object):
     """
     Mixin for forward-declared versions of Instance and Type.
     """
     def _resolve_string(self, string):
         """
         Find the specified class name by looking for it in the module in which
         our this_class attribute was defined.
         """
         modname = self.this_class.__module__
         return import_item('.'.join([modname, string]))
 
 
 class ForwardDeclaredType(ForwardDeclaredMixin, Type):
     """
     Forward-declared version of Type.
     """
     pass
 
 
 class ForwardDeclaredInstance(ForwardDeclaredMixin, Instance):
     """
     Forward-declared version of Instance.
     """
     pass
 
 
 class This(ClassBasedTraitType):
     """A trait for instances of the class containing this trait.
 
     Because how how and when class bodies are executed, the ``This``
     trait can only have a default value of None.  This, and because we
     always validate default values, ``allow_none`` is *always* true.
     """
 
     info_text = 'an instance of the same type as the receiver or None'
 
     def __init__(self, **metadata):
         super(This, self).__init__(None, **metadata)
 
     def validate(self, obj, value):
         # What if value is a superclass of obj.__class__?  This is
         # complicated if it was the superclass that defined the This
         # trait.
         if isinstance(value, self.this_class) or (value is None):
             return value
         else:
             self.error(obj, value)
 
 
 class Union(TraitType):
     """A trait type representing a Union type."""
 
     def __init__(self, trait_types, **metadata):
         """Construct a Union  trait.
 
         This trait allows values that are allowed by at least one of the
         specified trait types. A Union traitlet cannot have metadata on
         its own, besides the metadata of the listed types.
 
         Parameters
         ----------
         trait_types: sequence
             The list of trait types of length at least 1.
 
         Notes
         -----
         Union([Float(), Bool(), Int()]) attempts to validate the provided values
         with the validation function of Float, then Bool, and finally Int.
         """
         self.trait_types = trait_types
         self.info_text = " or ".join([tt.info_text for tt in self.trait_types])
         self.default_value = self.trait_types[0].get_default_value()
         super(Union, self).__init__(**metadata)
 
     def instance_init(self):
         for trait_type in self.trait_types:
             trait_type.name = self.name
             trait_type.this_class = self.this_class
             trait_type.instance_init()
         super(Union, self).instance_init()
 
     def validate(self, obj, value):
         for trait_type in self.trait_types:
             try:
                 v = trait_type._validate(obj, value)
                 self._metadata = trait_type._metadata
                 return v
             except TraitError:
                 continue
         self.error(obj, value)
 
     def __or__(self, other):
         if isinstance(other, Union):
             return Union(self.trait_types + other.trait_types)
         else:
             return Union(self.trait_types + [other])
 
 #-----------------------------------------------------------------------------
 # Basic TraitTypes implementations/subclasses
 #-----------------------------------------------------------------------------
 
 
 class Any(TraitType):
     default_value = None
     info_text = 'any value'
 
 
 class Int(TraitType):
     """An int trait."""
 
     default_value = 0
     info_text = 'an int'
 
     def validate(self, obj, value):
         if isinstance(value, int):
             return value
         self.error(obj, value)
 
 class CInt(Int):
     """A casting version of the int trait."""
 
     def validate(self, obj, value):
         try:
             return int(value)
         except:
             self.error(obj, value)
 
 if py3compat.PY3:
     Long, CLong = Int, CInt
     Integer = Int
 else:
     class Long(TraitType):
         """A long integer trait."""
 
         default_value = 0
         info_text = 'a long'
 
         def validate(self, obj, value):
             if isinstance(value, long):
                 return value
             if isinstance(value, int):
                 return long(value)
             self.error(obj, value)
 
 
     class CLong(Long):
         """A casting version of the long integer trait."""
 
         def validate(self, obj, value):
             try:
                 return long(value)
             except:
                 self.error(obj, value)
 
     class Integer(TraitType):
         """An integer trait.
 
         Longs that are unnecessary (<= sys.maxint) are cast to ints."""
 
         default_value = 0
         info_text = 'an integer'
 
         def validate(self, obj, value):
             if isinstance(value, int):
                 return value
             if isinstance(value, long):
                 # downcast longs that fit in int:
                 # note that int(n > sys.maxint) returns a long, so
                 # we don't need a condition on this cast
                 return int(value)
             if sys.platform == "cli":
                 from System import Int64
                 if isinstance(value, Int64):
                     return int(value)
             self.error(obj, value)
 
 
 class Float(TraitType):
     """A float trait."""
 
     default_value = 0.0
     info_text = 'a float'
 
     def validate(self, obj, value):
         if isinstance(value, float):
             return value
         if isinstance(value, int):
             return float(value)
         self.error(obj, value)
 
 
 class CFloat(Float):
     """A casting version of the float trait."""
 
     def validate(self, obj, value):
         try:
             return float(value)
         except:
             self.error(obj, value)
 
 class Complex(TraitType):
     """A trait for complex numbers."""
 
     default_value = 0.0 + 0.0j
     info_text = 'a complex number'
 
     def validate(self, obj, value):
         if isinstance(value, complex):
             return value
         if isinstance(value, (float, int)):
             return complex(value)
         self.error(obj, value)
 
 
 class CComplex(Complex):
     """A casting version of the complex number trait."""
 
     def validate (self, obj, value):
         try:
             return complex(value)
         except:
             self.error(obj, value)
 
 # We should always be explicit about whether we're using bytes or unicode, both
 # for Python 3 conversion and for reliable unicode behaviour on Python 2. So
 # we don't have a Str type.
 class Bytes(TraitType):
     """A trait for byte strings."""
 
     default_value = b''
     info_text = 'a bytes object'
 
     def validate(self, obj, value):
         if isinstance(value, bytes):
             return value
         self.error(obj, value)
 
 
 class CBytes(Bytes):
     """A casting version of the byte string trait."""
 
     def validate(self, obj, value):
         try:
             return bytes(value)
         except:
             self.error(obj, value)
 
 
 class Unicode(TraitType):
     """A trait for unicode strings."""
 
     default_value = u''
     info_text = 'a unicode string'
 
     def validate(self, obj, value):
         if isinstance(value, py3compat.unicode_type):
             return value
         if isinstance(value, bytes):
             try:
                 return value.decode('ascii', 'strict')
             except UnicodeDecodeError:
                 msg = "Could not decode {!r} for unicode trait '{}' of {} instance."
                 raise TraitError(msg.format(value, self.name, class_of(obj)))
         self.error(obj, value)
 
 
 class CUnicode(Unicode):
     """A casting version of the unicode trait."""
 
     def validate(self, obj, value):
         try:
             return py3compat.unicode_type(value)
         except:
             self.error(obj, value)
 
 
 class ObjectName(TraitType):
     """A string holding a valid object name in this version of Python.
 
     This does not check that the name exists in any scope."""
     info_text = "a valid object identifier in Python"
 
     if py3compat.PY3:
         # Python 3:
         coerce_str = staticmethod(lambda _,s: s)
 
     else:
         # Python 2:
         def coerce_str(self, obj, value):
             "In Python 2, coerce ascii-only unicode to str"
             if isinstance(value, unicode):
                 try:
                     return str(value)
                 except UnicodeEncodeError:
                     self.error(obj, value)
             return value
 
     def validate(self, obj, value):
         value = self.coerce_str(obj, value)
 
         if isinstance(value, string_types) and py3compat.isidentifier(value):
             return value
         self.error(obj, value)
 
 class DottedObjectName(ObjectName):
     """A string holding a valid dotted object name in Python, such as A.b3._c"""
     def validate(self, obj, value):
         value = self.coerce_str(obj, value)
 
         if isinstance(value, string_types) and py3compat.isidentifier(value, dotted=True):
             return value
         self.error(obj, value)
 
 
 class Bool(TraitType):
     """A boolean (True, False) trait."""
 
     default_value = False
     info_text = 'a boolean'
 
     def validate(self, obj, value):
         if isinstance(value, bool):
             return value
         self.error(obj, value)
 
 
 class CBool(Bool):
     """A casting version of the boolean trait."""
 
     def validate(self, obj, value):
         try:
             return bool(value)
         except:
             self.error(obj, value)
 
 
 class Enum(TraitType):
     """An enum that whose value must be in a given sequence."""
 
     def __init__(self, values, default_value=None, **metadata):
         self.values = values
         super(Enum, self).__init__(default_value, **metadata)
 
     def validate(self, obj, value):
         if value in self.values:
                 return value
         self.error(obj, value)
 
     def info(self):
         """ Returns a description of the trait."""
         result = 'any of ' + repr(self.values)
         if self.allow_none:
             return result + ' or None'
         return result
 
 class CaselessStrEnum(Enum):
     """An enum of strings that are caseless in validate."""
 
     def validate(self, obj, value):
         if not isinstance(value, py3compat.string_types):
             self.error(obj, value)
 
         for v in self.values:
             if v.lower() == value.lower():
                 return v
         self.error(obj, value)
 
 class Container(Instance):
     """An instance of a container (list, set, etc.)
 
     To be subclassed by overriding klass.
     """
     klass = None
     _cast_types = ()
     _valid_defaults = SequenceTypes
     _trait = None
 
     def __init__(self, trait=None, default_value=None, allow_none=False,
                 **metadata):
         """Create a container trait type from a list, set, or tuple.
 
         The default value is created by doing ``List(default_value)``,
         which creates a copy of the ``default_value``.
 
         ``trait`` can be specified, which restricts the type of elements
         in the container to that TraitType.
 
         If only one arg is given and it is not a Trait, it is taken as
         ``default_value``:
 
         ``c = List([1,2,3])``
 
         Parameters
         ----------
 
         trait : TraitType [ optional ]
             the type for restricting the contents of the Container.  If unspecified,
             types are not checked.
 
         default_value : SequenceType [ optional ]
             The default value for the Trait.  Must be list/tuple/set, and
             will be cast to the container type.
 
         allow_none : bool [ default False ]
             Whether to allow the value to be None
 
         **metadata : any
             further keys for extensions to the Trait (e.g. config)
 
         """
         # allow List([values]):
         if default_value is None and not is_trait(trait):
             default_value = trait
             trait = None
 
         if default_value is None:
             args = ()
         elif isinstance(default_value, self._valid_defaults):
             args = (default_value,)
         else:
             raise TypeError('default value of %s was %s' %(self.__class__.__name__, default_value))
 
         if is_trait(trait):
             self._trait = trait() if isinstance(trait, type) else trait
             self._trait.name = 'element'
         elif trait is not None:
             raise TypeError("`trait` must be a Trait or None, got %s"%repr_type(trait))
 
         super(Container,self).__init__(klass=self.klass, args=args,
                                   allow_none=allow_none, **metadata)
 
     def element_error(self, obj, element, validator):
         e = "Element of the '%s' trait of %s instance must be %s, but a value of %s was specified." \
             % (self.name, class_of(obj), validator.info(), repr_type(element))
         raise TraitError(e)
 
     def validate(self, obj, value):
         if isinstance(value, self._cast_types):
             value = self.klass(value)
         value = super(Container, self).validate(obj, value)
         if value is None:
             return value
 
         value = self.validate_elements(obj, value)
 
         return value
 
     def validate_elements(self, obj, value):
         validated = []
         if self._trait is None or isinstance(self._trait, Any):
             return value
         for v in value:
             try:
                 v = self._trait._validate(obj, v)
             except TraitError:
                 self.element_error(obj, v, self._trait)
             else:
                 validated.append(v)
         return self.klass(validated)
 
     def instance_init(self):
         if isinstance(self._trait, TraitType):
             self._trait.this_class = self.this_class
             self._trait.instance_init()
         super(Container, self).instance_init()
 
 
 class List(Container):
     """An instance of a Python list."""
     klass = list
     _cast_types = (tuple,)
 
     def __init__(self, trait=None, default_value=None, minlen=0, maxlen=sys.maxsize, **metadata):
         """Create a List trait type from a list, set, or tuple.
 
         The default value is created by doing ``List(default_value)``,
         which creates a copy of the ``default_value``.
 
         ``trait`` can be specified, which restricts the type of elements
         in the container to that TraitType.
 
         If only one arg is given and it is not a Trait, it is taken as
         ``default_value``:
 
         ``c = List([1,2,3])``
 
         Parameters
         ----------
 
         trait : TraitType [ optional ]
             the type for restricting the contents of the Container.  If unspecified,
             types are not checked.
 
         default_value : SequenceType [ optional ]
             The default value for the Trait.  Must be list/tuple/set, and
             will be cast to the container type.
 
         minlen : Int [ default 0 ]
             The minimum length of the input list
 
         maxlen : Int [ default sys.maxsize ]
             The maximum length of the input list
 
         allow_none : bool [ default False ]
             Whether to allow the value to be None
 
         **metadata : any
             further keys for extensions to the Trait (e.g. config)
 
         """
         self._minlen = minlen
         self._maxlen = maxlen
         super(List, self).__init__(trait=trait, default_value=default_value,
                                 **metadata)
 
     def length_error(self, obj, value):
         e = "The '%s' trait of %s instance must be of length %i <= L <= %i, but a value of %s was specified." \
             % (self.name, class_of(obj), self._minlen, self._maxlen, value)
         raise TraitError(e)
 
     def validate_elements(self, obj, value):
         length = len(value)
         if length < self._minlen or length > self._maxlen:
             self.length_error(obj, value)
 
         return super(List, self).validate_elements(obj, value)
 
     def validate(self, obj, value):
         value = super(List, self).validate(obj, value)
         value = self.validate_elements(obj, value)
         return value
 
 
 class Set(List):
     """An instance of a Python set."""
     klass = set
     _cast_types = (tuple, list)
 
 
 class Tuple(Container):
     """An instance of a Python tuple."""
     klass = tuple
     _cast_types = (list,)
 
     def __init__(self, *traits, **metadata):
         """Tuple(*traits, default_value=None, **medatata)
 
         Create a tuple from a list, set, or tuple.
 
         Create a fixed-type tuple with Traits:
 
         ``t = Tuple(Int, Str, CStr)``
 
         would be length 3, with Int,Str,CStr for each element.
 
         If only one arg is given and it is not a Trait, it is taken as
         default_value:
 
         ``t = Tuple((1,2,3))``
 
         Otherwise, ``default_value`` *must* be specified by keyword.
 
         Parameters
         ----------
 
         *traits : TraitTypes [ optional ]
             the tsype for restricting the contents of the Tuple.  If unspecified,
             types are not checked. If specified, then each positional argument
             corresponds to an element of the tuple.  Tuples defined with traits
             are of fixed length.
 
         default_value : SequenceType [ optional ]
             The default value for the Tuple.  Must be list/tuple/set, and
             will be cast to a tuple. If `traits` are specified, the
             `default_value` must conform to the shape and type they specify.
 
         allow_none : bool [ default False ]
             Whether to allow the value to be None
 
         **metadata : any
             further keys for extensions to the Trait (e.g. config)
 
         """
         default_value = metadata.pop('default_value', None)
         allow_none = metadata.pop('allow_none', True)
 
         # allow Tuple((values,)):
         if len(traits) == 1 and default_value is None and not is_trait(traits[0]):
             default_value = traits[0]
             traits = ()
 
         if default_value is None:
             args = ()
         elif isinstance(default_value, self._valid_defaults):
             args = (default_value,)
         else:
             raise TypeError('default value of %s was %s' %(self.__class__.__name__, default_value))
 
         self._traits = []
         for trait in traits:
             t = trait() if isinstance(trait, type) else trait
             t.name = 'element'
             self._traits.append(t)
 
         if self._traits and default_value is None:
             # don't allow default to be an empty container if length is specified
             args = None
         super(Container,self).__init__(klass=self.klass, args=args, **metadata)
 
     def validate_elements(self, obj, value):
         if not self._traits:
             # nothing to validate
             return value
         if len(value) != len(self._traits):
             e = "The '%s' trait of %s instance requires %i elements, but a value of %s was specified." \
                 % (self.name, class_of(obj), len(self._traits), repr_type(value))
             raise TraitError(e)
 
         validated = []
         for t, v in zip(self._traits, value):
             try:
                 v = t._validate(obj, v)
             except TraitError:
                 self.element_error(obj, v, t)
             else:
                 validated.append(v)
         return tuple(validated)
 
     def instance_init(self):
         for trait in self._traits:
             if isinstance(trait, TraitType):
                 trait.this_class = self.this_class
                 trait.instance_init()
         super(Container, self).instance_init()
 
 
 class Dict(Instance):
     """An instance of a Python dict."""
     _trait = None
 
     def __init__(self, trait=None, default_value=NoDefaultSpecified, allow_none=False, **metadata):
         """Create a dict trait type from a dict.
 
         The default value is created by doing ``dict(default_value)``,
         which creates a copy of the ``default_value``.
 
         trait : TraitType [ optional ]
             the type for restricting the contents of the Container.  If unspecified,
             types are not checked.
 
         default_value : SequenceType [ optional ]
             The default value for the Dict.  Must be dict, tuple, or None, and
             will be cast to a dict if not None. If `trait` is specified, the
             `default_value` must conform to the constraints it specifies.
 
         allow_none : bool [ default False ]
             Whether to allow the value to be None
 
         """
         if default_value is NoDefaultSpecified and trait is not None:
             if not is_trait(trait):
                 default_value = trait
                 trait = None
         if default_value is NoDefaultSpecified:
             default_value = {}
         if default_value is None:
             args = None
         elif isinstance(default_value, dict):
             args = (default_value,)
         elif isinstance(default_value, SequenceTypes):
             args = (default_value,)
         else:
             raise TypeError('default value of Dict was %s' % default_value)
 
         if is_trait(trait):
             self._trait = trait() if isinstance(trait, type) else trait
             self._trait.name = 'element'
         elif trait is not None:
             raise TypeError("`trait` must be a Trait or None, got %s"%repr_type(trait))
 
         super(Dict,self).__init__(klass=dict, args=args,
                                   allow_none=allow_none, **metadata)
 
     def element_error(self, obj, element, validator):
         e = "Element of the '%s' trait of %s instance must be %s, but a value of %s was specified." \
             % (self.name, class_of(obj), validator.info(), repr_type(element))
         raise TraitError(e)
 
     def validate(self, obj, value):
         value = super(Dict, self).validate(obj, value)
         if value is None:
             return value
         value = self.validate_elements(obj, value)
         return value
 
     def validate_elements(self, obj, value):
         if self._trait is None or isinstance(self._trait, Any):
             return value
         validated = {}
         for key in value:
             v = value[key]
             try:
                 v = self._trait._validate(obj, v)
             except TraitError:
                 self.element_error(obj, v, self._trait)
             else:
                 validated[key] = v
         return self.klass(validated)
 
     def instance_init(self):
         if isinstance(self._trait, TraitType):
             self._trait.this_class = self.this_class
             self._trait.instance_init()
         super(Dict, self).instance_init()
 
 
 class EventfulDict(Instance):
     """An instance of an EventfulDict."""
 
     def __init__(self, default_value={}, allow_none=False, **metadata):
         """Create a EventfulDict trait type from a dict.
 
         The default value is created by doing
         ``eventful.EvenfulDict(default_value)``, which creates a copy of the
         ``default_value``.
         """
         if default_value is None:
             args = None
         elif isinstance(default_value, dict):
             args = (default_value,)
         elif isinstance(default_value, SequenceTypes):
             args = (default_value,)
         else:
             raise TypeError('default value of EventfulDict was %s' % default_value)
 
         super(EventfulDict, self).__init__(klass=eventful.EventfulDict, args=args,
                                   allow_none=allow_none, **metadata)
 
 
 class EventfulList(Instance):
     """An instance of an EventfulList."""
 
     def __init__(self, default_value=None, allow_none=False, **metadata):
         """Create a EventfulList trait type from a dict.
 
         The default value is created by doing 
         ``eventful.EvenfulList(default_value)``, which creates a copy of the 
         ``default_value``.
         """
         if default_value is None:
             args = ((),)
         else:
             args = (default_value,)
 
         super(EventfulList, self).__init__(klass=eventful.EventfulList, args=args,
                                   allow_none=allow_none, **metadata)
 
 
 class TCPAddress(TraitType):
     """A trait for an (ip, port) tuple.
 
     This allows for both IPv4 IP addresses as well as hostnames.
     """
 
     default_value = ('127.0.0.1', 0)
     info_text = 'an (ip, port) tuple'
 
     def validate(self, obj, value):
         if isinstance(value, tuple):
             if len(value) == 2:
                 if isinstance(value[0], py3compat.string_types) and isinstance(value[1], int):
                     port = value[1]
                     if port >= 0 and port <= 65535:
                         return value
         self.error(obj, value)
 
 class CRegExp(TraitType):
     """A casting compiled regular expression trait.
 
     Accepts both strings and compiled regular expressions. The resulting
     attribute will be a compiled regular expression."""
 
     info_text = 'a regular expression'
 
     def validate(self, obj, value):
         try:
             return re.compile(value)
         except:
             self.error(obj, value)