Fixing bugs and adding comment

IPython/testing/globalipapp.py

@@ -1,174 +1,174 b''
 """Global IPython app to support test running.
 
 We must start our own ipython object and heavily muck with it so that all the
 modifications IPython makes to system behavior don't send the doctest machinery
 into a fit.  This code should be considered a gross hack, but it gets the job
 done.
 """
 
 from __future__ import absolute_import
 
 #-----------------------------------------------------------------------------
 #  Copyright (C) 2009  The IPython Development Team
 #
 #  Distributed under the terms of the BSD License.  The full license is in
 #  the file COPYING, distributed as part of this software.
 #-----------------------------------------------------------------------------
 
 #-----------------------------------------------------------------------------
 # Imports
 #-----------------------------------------------------------------------------
 
 import __builtin__
 import commands
 import os
 import sys
 
 from . import tools
 
 #-----------------------------------------------------------------------------
 # Functions
 #-----------------------------------------------------------------------------
 
 # Hack to modify the %run command so we can sync the user's namespace with the
 # test globals.  Once we move over to a clean magic system, this will be done
 # with much less ugliness.
 
 class py_file_finder(object):
     def __init__(self,test_filename):
         self.test_filename = test_filename
         
     def __call__(self,name):
         from IPython.utils.path import get_py_filename
         try:
             return get_py_filename(name)
         except IOError:
             test_dir = os.path.dirname(self.test_filename)
             new_path = os.path.join(test_dir,name)
             return get_py_filename(new_path)
     
 
 def _run_ns_sync(self,arg_s,runner=None):
     """Modified version of %run that syncs testing namespaces.
 
     This is strictly needed for running doctests that call %run.
     """
     #print >> sys.stderr,  'in run_ns_sync', arg_s  # dbg
     
     _ip = get_ipython()
     finder = py_file_finder(arg_s)
     out = _ip.magic_run_ori(arg_s,runner,finder)
     return out
 
 
 class ipnsdict(dict):
     """A special subclass of dict for use as an IPython namespace in doctests.
 
     This subclass adds a simple checkpointing capability so that when testing
     machinery clears it (we use it as the test execution context), it doesn't
     get completely destroyed.
     """
     
     def __init__(self,*a):
         dict.__init__(self,*a)
         self._savedict = {}
         
     def clear(self):
         dict.clear(self)
         self.update(self._savedict)
         
     def _checkpoint(self):
         self._savedict.clear()
         self._savedict.update(self)
 
     def update(self,other):
         self._checkpoint()
         dict.update(self,other)
 
         # If '_' is in the namespace, python won't set it when executing code,
         # and we have examples that test it.  So we ensure that the namespace
         # is always 'clean' of it before it's used for test code execution.
         self.pop('_',None)
 
         # The builtins namespace must *always* be the real __builtin__ module,
         # else weird stuff happens.  The main ipython code does have provisions
         # to ensure this after %run, but since in this class we do some
         # aggressive low-level cleaning of the execution namespace, we need to
         # correct for that ourselves, to ensure consitency with the 'real'
         # ipython.
         self['__builtins__'] = __builtin__
 
 
 def get_ipython():
     # This will get replaced by the real thing once we start IPython below
     return start_ipython()
 
 
 def start_ipython():
     """Start a global IPython shell, which we need for IPython-specific syntax.
     """
     global get_ipython
 
     # This function should only ever run once!
     if hasattr(start_ipython, 'already_called'):
         return
     start_ipython.already_called = True
 
     # Ok,  first time we're called, go ahead
     from IPython.core import iplib
     
     def xsys(cmd):
         """Execute a command and print its output.
 
         This is just a convenience function to replace the IPython system call
         with one that is more doctest-friendly.
         """
         cmd = _ip.var_expand(cmd,depth=1)
         sys.stdout.write(commands.getoutput(cmd))
         sys.stdout.flush()
 
     # Store certain global objects that IPython modifies
     _displayhook = sys.displayhook
     _excepthook = sys.excepthook
     _main = sys.modules.get('__main__')
 
     # Create custom argv and namespaces for our IPython to be test-friendly
     config = tools.default_config()
 
     # Create and initialize our test-friendly IPython instance.
-    shell = iplib.InteractiveShell(
+    shell = iplib.InteractiveShell.instance(
         config=config, 
         user_ns=ipnsdict(), user_global_ns={}
     )
 
     # A few more tweaks needed for playing nicely with doctests...
     
     # These traps are normally only active for interactive use, set them
     # permanently since we'll be mocking interactive sessions.
     shell.builtin_trap.set()
 
     # Set error printing to stdout so nose can doctest exceptions
     shell.InteractiveTB.out_stream = 'stdout'
     
     # Modify the IPython system call with one that uses getoutput, so that we
     # can capture subcommands and print them to Python's stdout, otherwise the
     # doctest machinery would miss them.
     shell.system = xsys
 
     # IPython is ready, now clean up some global state...
     
     # Deactivate the various python system hooks added by ipython for
     # interactive convenience so we don't confuse the doctest system
     sys.modules['__main__'] = _main
     sys.displayhook = _displayhook
     sys.excepthook = _excepthook
 
     # So that ipython magics and aliases can be doctested (they work by making
     # a call into a global _ip object).  Also make the top-level get_ipython
     # now return this without recursively calling here again.
     _ip = shell
     get_ipython = _ip.get_ipython
     __builtin__._ip = _ip
     __builtin__.get_ipython = get_ipython
 
     return _ip

IPython/utils/traitlets.py

@@ -1,1048 +1,1050 b''
 #!/usr/bin/env python
 # 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.
 
 Authors:
 
 * Brian Granger
 * Enthought, Inc.  Some of the code in this file comes from enthought.traits
   and is licensed under the BSD license.  Also, many of the ideas also come
   from enthought.traits even though our implementation is very different.
 """
 
 #-----------------------------------------------------------------------------
 #  Copyright (C) 2008-2009  The IPython Development Team
 #
 #  Distributed under the terms of the BSD License.  The full license is in
 #  the file COPYING, distributed as part of this software.
 #-----------------------------------------------------------------------------
 
 #-----------------------------------------------------------------------------
 # Imports
 #-----------------------------------------------------------------------------
 
 
 import inspect
 import sys
 import types
 from types import (
     InstanceType, ClassType, FunctionType,
     ListType, TupleType
 )
 
 def import_item(name):
     """Import and return bar given the string foo.bar."""
     package = '.'.join(name.split('.')[0:-1])
     obj = name.split('.')[-1]
     execString = 'from %s import %s' % (package, obj)
     try:
         exec execString
     except SyntaxError:
         raise ImportError("Invalid class specification: %s" % name)
     exec 'temp = %s' % obj
     return temp
 
 
 ClassTypes = (ClassType, type)
 
 SequenceTypes = (ListType, TupleType)
 
 #-----------------------------------------------------------------------------
 # 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, basestring ):
         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 the_type is InstanceType:
         # Old-style class.
         the_type = obj.__class__
     msg = '%r %r' % (obj, the_type)
     return msg
 
 
 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, str):
         return [name]
     elif name is None:
         return ['anytrait']
     elif isinstance(name, (list, tuple)):
         for n in name:
             assert isinstance(n, str), "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
 
 
 #-----------------------------------------------------------------------------
 # 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
     info_text = 'any value'
 
     def __init__(self, default_value=NoDefaultSpecified, **metadata):
         """Create a TraitType.
         """
         if default_value is not NoDefaultSpecified:
             self.default_value = 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."""
         dv = self.default_value
         return dv
 
     def instance_init(self, obj):
         """This is called by :meth:`HasTraits.__new__` to finish init'ing.
 
         Some stages of initialization must be delayed until the parent
         :class:`HasTraits` instance has been created.  This method is
         called in :meth:`HasTraits.__new__` after the instance has been
         created.
 
         This method trigger the creation and validation of default values
         and also things like the resolution of str given class names in 
         :class:`Type` and :class`Instance`.
 
         Parameters
         ----------
         obj : :class:`HasTraits` instance
             The parent :class:`HasTraits` instance that has just been
             created.
         """
         self.set_default_value(obj)
 
     def set_default_value(self, obj):
         """Set the default value on a per instance basis.
 
         This method is called by :meth:`instance_init` to create and
         validate the default value.  The creation and validation of 
         default values must be delayed until the parent :class:`HasTraits`
         class has been instantiated.
         """
         dv = self.get_default_value()
         newdv = self._validate(obj, dv)
         obj._trait_values[self.name] = newdv
 
     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:
                 # 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)
         old_value = self.__get__(obj)
         if old_value != new_value:
             obj._trait_values[self.name] = new_value
             obj._notify_trait(self.name, old_value, new_value)
 
     def _validate(self, obj, value):
         if hasattr(self, 'validate'):
             return self.validate(obj, value)
         elif hasattr(self, 'is_valid_for'):
             valid = self.is_valid_for(value)
             if valid:
                 return value
             else:
                 raise TraitError('invalid value for type: %r' % value)
         elif hasattr(self, 'value_for'):
             return self.value_for(value)
         else:
             return value
 
     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):
         return getattr(self, '_metadata', {}).get(key, None)
 
     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 classdict.iteritems():
             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 classdict.iteritems():
             if isinstance(v, TraitType):
                 v.this_class = cls
         super(MetaHasTraits, cls).__init__(name, bases, classdict)
 
 class HasTraits(object):
 
     __metaclass__ = MetaHasTraits
 
     def __new__(cls, **kw):
         # This is needed because in Python 2.6 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 = {}
         # 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(inst)
 
         return inst
 
     def __init__(self, **kw):
         # Allow trait values to be set using keyword arguments.
+        # We need to use setattr for this to trigger validation and
+        # notifications.
         for key, value in kw.iteritems():
             setattr(self, key, value)
 
     def _notify_trait(self, name, old_value, new_value):
 
         # First dynamic ones
         callables = self._trait_notifiers.get(name,[])
         more_callables = self._trait_notifiers.get('anytrait',[])
         callables.extend(more_callables)
 
         # 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 not self._trait_notifiers.has_key(name):
             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 self._trait_notifiers.has_key(name):
             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)
 
     def trait_names(self, **metadata):
         """Get a list of all the names of this classes traits."""
         return self.traits(**metadata).keys()
 
     def traits(self, **metadata):
         """Get a list of all the traits of this class.
 
         The TraitTypes returned don't know anything about the values
         that the various HasTrait's instances are holding.
 
         This follows the same algorithm as traits does and does not allow
         for any simple way of specifying merely that a metadata name
         exists, but has any value.  This is 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):
         """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)
 
 #-----------------------------------------------------------------------------
 # Actual TraitTypes implementations/subclasses
 #-----------------------------------------------------------------------------
 
 #-----------------------------------------------------------------------------
 # TraitTypes subclasses for handling classes and instances of classes
 #-----------------------------------------------------------------------------
 
 
 class ClassBasedTraitType(TraitType):
     """A trait with error reporting for Type, Instance and This."""
 
     def error(self, obj, value):
         kind = type(value)
         if kind is InstanceType:
             msg = 'class %s' % value.__class__.__name__
         else:
             msg = '%s (i.e. %s)' % ( str( kind )[1:-1], repr( value ) )
 
         super(ClassBasedTraitType, self).error(obj, msg)
 
 
 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 : boolean
             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, basestring)):
             raise TraitError("A Type trait must specify a class.")
 
         self.klass       = klass
         self._allow_none = allow_none
 
         super(Type, self).__init__(default_value, **metadata)
 
     def validate(self, obj, value):
         """Validates that the value is a valid object instance."""
         try:
             if issubclass(value, self.klass):
                 return value
         except:
             if (value is None) and (self._allow_none):
                 return value
 
         self.error(obj, value)
 
     def info(self):
         """ Returns a description of the trait."""
         if isinstance(self.klass, basestring):
             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, obj):
         self._resolve_classes()
         super(Type, self).instance_init(obj)
 
     def _resolve_classes(self):
         if isinstance(self.klass, basestring):
             self.klass = import_item(self.klass)
         if isinstance(self.default_value, basestring):
             self.default_value = import_item(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.
     """
 
     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 sublclasses.  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
             Indicates whether None is allowed as a value.
 
         Default Value
         -------------
         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 either ``args`` or ``kw`` is 
         not (but not both), None is replace by ``()`` or ``{}``.
         """
 
         self._allow_none = allow_none
 
         if (klass is None) or (not (inspect.isclass(klass) or isinstance(klass, basestring))):
             raise TraitError('The klass argument must be a class'
                                 ' you gave: %r' % klass)
         self.klass = 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, **metadata)
 
     def validate(self, obj, value):
         if value is None:
             if self._allow_none:
                 return value
             self.error(obj, value)
 
         if isinstance(value, self.klass):
             return value
         else:
             self.error(obj, value)
 
     def info(self):
         if isinstance(self.klass, basestring):
             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, obj):
         self._resolve_classes()
         super(Instance, self).instance_init(obj)
 
     def _resolve_classes(self):
         if isinstance(self.klass, basestring):
             self.klass = import_item(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 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)
 
 
 #-----------------------------------------------------------------------------
 # Basic TraitTypes implementations/subclasses
 #-----------------------------------------------------------------------------
 
 
 class Any(TraitType):
     default_value = None
     info_text = 'any value'
 
 
 class Int(TraitType):
     """A integer trait."""
 
     evaluate = int
     default_value = 0
     info_text = 'an integer'
 
     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)
 
 
 class Long(TraitType):
     """A long integer trait."""
 
     evaluate = long
     default_value = 0L
     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 Float(TraitType):
     """A float trait."""
 
     evaluate = float
     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."""
 
     evaluate = complex
     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)
 
 
 class Str(TraitType):
     """A trait for strings."""
 
     evaluate = lambda x: x
     default_value = ''
     info_text = 'a string'
 
     def validate(self, obj, value):
         if isinstance(value, str):
             return value
         self.error(obj, value)
 
 
 class CStr(Str):
     """A casting version of the string trait."""
 
     def validate(self, obj, value):
         try:
             return str(value)
         except:
             try:
                 return unicode(value)
             except:
                 self.error(obj, value)
 
 
 class Unicode(TraitType):
     """A trait for unicode strings."""
 
     evaluate = unicode
     default_value = u''
     info_text = 'a unicode string'
 
     def validate(self, obj, value):
         if isinstance(value, unicode):
             return value
         if isinstance(value, str):
             return unicode(value)
         self.error(obj, value)
 
 
 class CUnicode(Unicode):
     """A casting version of the unicode trait."""
 
     def validate(self, obj, value):
         try:
             return unicode(value)
         except:
             self.error(obj, value)
 
 
 class Bool(TraitType):
     """A boolean (True, False) trait."""
     evaluate = bool
     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, allow_none=True, **metadata):
         self.values = values
         self._allow_none = allow_none
         super(Enum, self).__init__(default_value, **metadata)
 
     def validate(self, obj, value):
         if value is None:
             if self._allow_none:
                 return 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 value is None:
             if self._allow_none:
                 return value
 
         if not isinstance(value, str):
             self.error(obj, value)
 
         for v in self.values:
             if v.lower() == value.lower():
                 return v
         self.error(obj, value)
 
 
 class List(Instance):
     """An instance of a Python list."""
 
     def __init__(self, default_value=None, allow_none=True, **metadata):
         """Create a list trait type from a list or tuple.
 
         The default value is created by doing ``list(default_value)``, 
         which creates a copy of the ``default_value``.
         """
         if default_value is None:
             args = ((),)
         elif isinstance(default_value, SequenceTypes):
             args = (default_value,)
         else:
             raise TypeError('default value of List was %s' % default_value)
 
         super(List,self).__init__(klass=list, args=args, 
                                   allow_none=allow_none, **metadata)
 
 
 class Dict(Instance):
     """An instance of a Python dict."""
 
     def __init__(self, default_value=None, allow_none=True, **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``.
         """
         if default_value is None:
             args = ((),)
         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)
 
         super(Dict,self).__init__(klass=dict, args=args, 
                                   allow_none=allow_none, **metadata)