# encoding: utf-8 """ A lightweight Traits like module. This is designed to provide a lightweight, simple, pure Python version of many of the capabilities of enthought.traits. This includes: * Validation * Type specification with defaults * Static and dynamic notification * Basic predefined types * An API that is similar to enthought.traits We don't support: * Delegation * Automatic GUI generation * A full set of trait types. Most importantly, we don't provide container traits (list, dict, tuple) that can trigger notifications if their contents change. * API compatibility with enthought.traits There are also some important difference in our design: * enthought.traits does not validate default values. We do. We choose to create this module because we need these capabilities, but we need them to be pure Python so they work in all Python implementations, including Jython and IronPython. Inheritance diagram: .. inheritance-diagram:: IPython.utils.traitlets :parts: 3 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 " 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, *args, **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, *args, **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 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): # Command line arguments come in as strings, let's make them into # lists so we can proceed with validation if isinstance(value, basestring): value = value.split(',') 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)