changes for ironpython

IPython/core/displayhook.py

@@ -1,270 +1,275 b''
 # -*- coding: utf-8 -*-
 """Displayhook for IPython.
 
 This defines a callable class that IPython uses for `sys.displayhook`.
 
 Authors:
 
 * Fernando Perez
 * Brian Granger
 * Robert Kern
 """
 
 #-----------------------------------------------------------------------------
 #       Copyright (C) 2008-2011 The IPython Development Team
 #       Copyright (C) 2001-2007 Fernando Perez <[e-mail]>
 #
 #  Distributed under the terms of the BSD License.  The full license is in
 #  the file COPYING, distributed as part of this software.
 #-----------------------------------------------------------------------------
 
 #-----------------------------------------------------------------------------
 # Imports
 #-----------------------------------------------------------------------------
 from __future__ import print_function
 
 import __builtin__
 
+import sys
+
+
 from IPython.config.configurable import Configurable
 from IPython.utils import io
 from IPython.utils.traitlets import Instance, List
 from IPython.utils.warn import warn
 
 #-----------------------------------------------------------------------------
 # Main displayhook class
 #-----------------------------------------------------------------------------
 
 # TODO: Move the various attributes (cache_size, [others now moved]). Some
 # of these are also attributes of InteractiveShell. They should be on ONE object
 # only and the other objects should ask that one object for their values.
 
 class DisplayHook(Configurable):
     """The custom IPython displayhook to replace sys.displayhook.
 
     This class does many things, but the basic idea is that it is a callable
     that gets called anytime user code returns a value.
     """
 
     shell = Instance('IPython.core.interactiveshell.InteractiveShellABC')
 
     def __init__(self, shell=None, cache_size=1000, config=None):
         super(DisplayHook, self).__init__(shell=shell, config=config)
 
         cache_size_min = 3
         if cache_size <= 0:
             self.do_full_cache = 0
             cache_size = 0
         elif cache_size < cache_size_min:
             self.do_full_cache = 0
             cache_size = 0
             warn('caching was disabled (min value for cache size is %s).' %
                  cache_size_min,level=3)
         else:
             self.do_full_cache = 1
 
         self.cache_size = cache_size
 
         # we need a reference to the user-level namespace
         self.shell = shell
         
         self._,self.__,self.___ = '','',''
 
         # these are deliberately global:
         to_user_ns = {'_':self._,'__':self.__,'___':self.___}
         self.shell.user_ns.update(to_user_ns)
 
     @property
     def prompt_count(self):
         return self.shell.execution_count
 
     #-------------------------------------------------------------------------
     # Methods used in __call__. Override these methods to modify the behavior
     # of the displayhook.
     #-------------------------------------------------------------------------
 
     def check_for_underscore(self):
         """Check if the user has set the '_' variable by hand."""
         # If something injected a '_' variable in __builtin__, delete
         # ipython's automatic one so we don't clobber that.  gettext() in
         # particular uses _, so we need to stay away from it.
         if '_' in __builtin__.__dict__:
             try:
                 del self.shell.user_ns['_']
             except KeyError:
                 pass
 
     def quiet(self):
         """Should we silence the display hook because of ';'?"""
         # do not print output if input ends in ';'
         try:
             cell = self.shell.history_manager.input_hist_parsed[self.prompt_count]
             if cell.rstrip().endswith(';'):
                 return True
         except IndexError:
             # some uses of ipshellembed may fail here
             pass
         return False
 
     def start_displayhook(self):
         """Start the displayhook, initializing resources."""
         pass
 
     def write_output_prompt(self):
         """Write the output prompt.
 
         The default implementation simply writes the prompt to
         ``io.stdout``.
         """
         # Use write, not print which adds an extra space.
         io.stdout.write(self.shell.separate_out)
         outprompt = self.shell.prompt_manager.render('out')
         if self.do_full_cache:
             io.stdout.write(outprompt)
 
     def compute_format_data(self, result):
         """Compute format data of the object to be displayed.
 
         The format data is a generalization of the :func:`repr` of an object.
         In the default implementation the format data is a :class:`dict` of
         key value pair where the keys are valid MIME types and the values
         are JSON'able data structure containing the raw data for that MIME
         type. It is up to frontends to determine pick a MIME to to use and
         display that data in an appropriate manner.
 
         This method only computes the format data for the object and should
         NOT actually print or write that to a stream.
 
         Parameters
         ----------
         result : object
             The Python object passed to the display hook, whose format will be
             computed.
 
         Returns
         -------
         format_data : dict
             A :class:`dict` whose keys are valid MIME types and values are
             JSON'able raw data for that MIME type. It is recommended that
             all return values of this should always include the "text/plain"
             MIME type representation of the object.
         """
         return self.shell.display_formatter.format(result)
 
     def write_format_data(self, format_dict):
         """Write the format data dict to the frontend.
 
         This default version of this method simply writes the plain text
         representation of the object to ``io.stdout``. Subclasses should
         override this method to send the entire `format_dict` to the
         frontends.
 
         Parameters
         ----------
         format_dict : dict
             The format dict for the object passed to `sys.displayhook`.
         """
         # We want to print because we want to always make sure we have a
         # newline, even if all the prompt separators are ''. This is the
         # standard IPython behavior.
         result_repr = format_dict['text/plain']
         if '\n' in result_repr:
             # So that multi-line strings line up with the left column of
             # the screen, instead of having the output prompt mess up
             # their first line.
             # We use the prompt template instead of the expanded prompt
             # because the expansion may add ANSI escapes that will interfere
             # with our ability to determine whether or not we should add
             # a newline.
             prompt_template = self.shell.prompt_manager.out_template
             if prompt_template and not prompt_template.endswith('\n'):
                 # But avoid extraneous empty lines.
                 result_repr = '\n' + result_repr
 
         print(result_repr, file=io.stdout)
 
     def update_user_ns(self, result):
         """Update user_ns with various things like _, __, _1, etc."""
 
         # Avoid recursive reference when displaying _oh/Out
         if result is not self.shell.user_ns['_oh']:
             if len(self.shell.user_ns['_oh']) >= self.cache_size and self.do_full_cache:
                 warn('Output cache limit (currently '+
                       repr(self.cache_size)+' entries) hit.\n'
                      'Flushing cache and resetting history counter...\n'
                      'The only history variables available will be _,__,___ and _1\n'
                      'with the current result.')
 
                 self.flush()
             # Don't overwrite '_' and friends if '_' is in __builtin__ (otherwise
             # we cause buggy behavior for things like gettext).
 
             if '_' not in __builtin__.__dict__:
                 self.___ = self.__
                 self.__ = self._
                 self._ = result
                 self.shell.push({'_':self._,
                                  '__':self.__,
                                 '___':self.___}, interactive=False)
 
             # hackish access to top-level  namespace to create _1,_2... dynamically
             to_main = {}
             if self.do_full_cache:
                 new_result = '_'+repr(self.prompt_count)
                 to_main[new_result] = result
                 self.shell.push(to_main, interactive=False)
                 self.shell.user_ns['_oh'][self.prompt_count] = result
 
     def log_output(self, format_dict):
         """Log the output."""
         if self.shell.logger.log_output:
             self.shell.logger.log_write(format_dict['text/plain'], 'output')
         self.shell.history_manager.output_hist_reprs[self.prompt_count] = \
                                                     format_dict['text/plain']
 
     def finish_displayhook(self):
         """Finish up all displayhook activities."""
         io.stdout.write(self.shell.separate_out2)
         io.stdout.flush()
 
     def __call__(self, result=None):
         """Printing with history cache management.
 
         This is invoked everytime the interpreter needs to print, and is
         activated by setting the variable sys.displayhook to it.
         """
         self.check_for_underscore()
         if result is not None and not self.quiet():
             self.start_displayhook()
             self.write_output_prompt()
             format_dict = self.compute_format_data(result)
             self.write_format_data(format_dict)
             self.update_user_ns(result)
             self.log_output(format_dict)
             self.finish_displayhook()
 
     def flush(self):
         if not self.do_full_cache:
             raise ValueError("You shouldn't have reached the cache flush "
                              "if full caching is not enabled!")
         # delete auto-generated vars from global namespace
 
         for n in range(1,self.prompt_count + 1):
             key = '_'+repr(n)
             try:
                 del self.shell.user_ns[key]
             except: pass
         # In some embedded circumstances, the user_ns doesn't have the
         # '_oh' key set up.
         oh = self.shell.user_ns.get('_oh', None)
         if oh is not None:
             oh.clear()
 
         # Release our own references to objects:
         self._, self.__, self.___ = '', '', ''
 
         if '_' not in __builtin__.__dict__:
             self.shell.user_ns.update({'_':None,'__':None, '___':None})
         import gc
         # TODO: Is this really needed?
+        # IronPython blocks here forever
+        if sys.platform != "cli":
         gc.collect()
 

IPython/utils/traitlets.py

@@ -1,1430 +1,1434 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.
 
 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) 2008-2011  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 re
 import sys
 import types
 from types import FunctionType
 try:
     from types import ClassType, InstanceType
     ClassTypes = (ClassType, type)
 except:
     ClassTypes = (type,)
 
 from .importstring import import_item
 from IPython.utils import py3compat
 
 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, 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 (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, 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."""
         return self.default_value
 
     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.
         """
         # 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.
             dv = self.get_default_value()
             newdv = self._validate(obj, dv)
             obj._trait_values[self.name] = newdv
             return
         # Complete the dynamic initialization.
         obj._trait_dyn_inits[self.name] = cls.__dict__[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:
                     value = obj._trait_dyn_inits[self.name](obj)
                     # FIXME: Do we really validate here?
                     value = self._validate(obj, value)
                     obj._trait_values[self.name] = value
                     return value
                 else:
                     raise TraitError('Unexpected error in TraitType: '
                         'both default value and dynamic initializer are '
                         'absent.')
             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)
         old_value = self.__get__(obj)
         obj._trait_values[self.name] = new_value
         if old_value != 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 = {}
         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(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 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 classes 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 list of all the traits of this class.
 
         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.
 
         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(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 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 (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 : 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):
     """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 = 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 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
-            elif isinstance(value, long):
+            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 string'
 
     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, unicode):
             return value
         if isinstance(value, bytes):
             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 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, str) 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, str) 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, 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, basestring):
             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
     _valid_defaults = SequenceTypes
     _trait = None
 
     def __init__(self, trait=None, default_value=None, allow_none=True,
                 **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 True ]
             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):
         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)
 
 
 class List(Container):
     """An instance of a Python list."""
     klass = list
 
     def __init__(self, trait=None, default_value=None, minlen=0, maxlen=sys.maxsize,
                 allow_none=True, **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 True ]
             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,
                                 allow_none=allow_none, **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)
 
 
 class Set(Container):
     """An instance of a Python set."""
     klass = set
 
 class Tuple(Container):
     """An instance of a Python tuple."""
     klass = tuple
 
     def __init__(self, *traits, **metadata):
         """Tuple(*traits, default_value=None, allow_none=True, **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 True ]
             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,
                                   allow_none=allow_none, **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)
 
 
 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)
 
 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], basestring) 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)