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			308 lines
		
	
	
	
		
			9.8 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			308 lines
		
	
	
	
		
			9.8 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
"""
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Define names for built-in types that aren't directly accessible as a builtin.
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"""
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import sys
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# Iterators in Python aren't a matter of type but of protocol.  A large
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# and changing number of builtin types implement *some* flavor of
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# iterator.  Don't check the type!  Use hasattr to check for both
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# "__iter__" and "__next__" attributes instead.
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def _f(): pass
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FunctionType = type(_f)
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LambdaType = type(lambda: None)         # Same as FunctionType
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CodeType = type(_f.__code__)
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MappingProxyType = type(type.__dict__)
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SimpleNamespace = type(sys.implementation)
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def _cell_factory():
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    a = 1
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    def f():
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        nonlocal a
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    return f.__closure__[0]
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CellType = type(_cell_factory())
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def _g():
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    yield 1
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GeneratorType = type(_g())
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async def _c(): pass
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_c = _c()
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CoroutineType = type(_c)
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_c.close()  # Prevent ResourceWarning
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async def _ag():
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    yield
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_ag = _ag()
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AsyncGeneratorType = type(_ag)
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class _C:
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    def _m(self): pass
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MethodType = type(_C()._m)
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BuiltinFunctionType = type(len)
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BuiltinMethodType = type([].append)     # Same as BuiltinFunctionType
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WrapperDescriptorType = type(object.__init__)
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MethodWrapperType = type(object().__str__)
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MethodDescriptorType = type(str.join)
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ClassMethodDescriptorType = type(dict.__dict__['fromkeys'])
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ModuleType = type(sys)
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try:
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    raise TypeError
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except TypeError:
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    tb = sys.exc_info()[2]
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    TracebackType = type(tb)
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    FrameType = type(tb.tb_frame)
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    tb = None; del tb
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# For Jython, the following two types are identical
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GetSetDescriptorType = type(FunctionType.__code__)
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MemberDescriptorType = type(FunctionType.__globals__)
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del sys, _f, _g, _C, _c, _ag  # Not for export
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# Provide a PEP 3115 compliant mechanism for class creation
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def new_class(name, bases=(), kwds=None, exec_body=None):
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    """Create a class object dynamically using the appropriate metaclass."""
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    resolved_bases = resolve_bases(bases)
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    meta, ns, kwds = prepare_class(name, resolved_bases, kwds)
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    if exec_body is not None:
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        exec_body(ns)
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    if resolved_bases is not bases:
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        ns['__orig_bases__'] = bases
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    return meta(name, resolved_bases, ns, **kwds)
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def resolve_bases(bases):
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    """Resolve MRO entries dynamically as specified by PEP 560."""
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    new_bases = list(bases)
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    updated = False
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    shift = 0
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    for i, base in enumerate(bases):
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        if isinstance(base, type):
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            continue
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        if not hasattr(base, "__mro_entries__"):
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            continue
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        new_base = base.__mro_entries__(bases)
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        updated = True
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        if not isinstance(new_base, tuple):
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            raise TypeError("__mro_entries__ must return a tuple")
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        else:
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            new_bases[i+shift:i+shift+1] = new_base
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            shift += len(new_base) - 1
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    if not updated:
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        return bases
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    return tuple(new_bases)
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def prepare_class(name, bases=(), kwds=None):
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    """Call the __prepare__ method of the appropriate metaclass.
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    Returns (metaclass, namespace, kwds) as a 3-tuple
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    *metaclass* is the appropriate metaclass
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    *namespace* is the prepared class namespace
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    *kwds* is an updated copy of the passed in kwds argument with any
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    'metaclass' entry removed. If no kwds argument is passed in, this will
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    be an empty dict.
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    """
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    if kwds is None:
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        kwds = {}
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    else:
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        kwds = dict(kwds) # Don't alter the provided mapping
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    if 'metaclass' in kwds:
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        meta = kwds.pop('metaclass')
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    else:
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        if bases:
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            meta = type(bases[0])
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        else:
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            meta = type
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    if isinstance(meta, type):
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        # when meta is a type, we first determine the most-derived metaclass
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        # instead of invoking the initial candidate directly
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        meta = _calculate_meta(meta, bases)
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    if hasattr(meta, '__prepare__'):
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        ns = meta.__prepare__(name, bases, **kwds)
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    else:
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        ns = {}
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    return meta, ns, kwds
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def _calculate_meta(meta, bases):
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    """Calculate the most derived metaclass."""
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    winner = meta
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    for base in bases:
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        base_meta = type(base)
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        if issubclass(winner, base_meta):
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            continue
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        if issubclass(base_meta, winner):
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            winner = base_meta
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            continue
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        # else:
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        raise TypeError("metaclass conflict: "
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                        "the metaclass of a derived class "
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                        "must be a (non-strict) subclass "
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                        "of the metaclasses of all its bases")
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    return winner
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class DynamicClassAttribute:
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    """Route attribute access on a class to __getattr__.
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    This is a descriptor, used to define attributes that act differently when
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    accessed through an instance and through a class.  Instance access remains
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    normal, but access to an attribute through a class will be routed to the
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    class's __getattr__ method; this is done by raising AttributeError.
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    This allows one to have properties active on an instance, and have virtual
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    attributes on the class with the same name.  (Enum used this between Python
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    versions 3.4 - 3.9 .)
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    Subclass from this to use a different method of accessing virtual attributes
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    and still be treated properly by the inspect module. (Enum uses this since
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    Python 3.10 .)
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    """
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    def __init__(self, fget=None, fset=None, fdel=None, doc=None):
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        self.fget = fget
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        self.fset = fset
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        self.fdel = fdel
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        # next two lines make DynamicClassAttribute act the same as property
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        self.__doc__ = doc or fget.__doc__
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        self.overwrite_doc = doc is None
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        # support for abstract methods
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        self.__isabstractmethod__ = bool(getattr(fget, '__isabstractmethod__', False))
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    def __get__(self, instance, ownerclass=None):
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        if instance is None:
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            if self.__isabstractmethod__:
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                return self
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            raise AttributeError()
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        elif self.fget is None:
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            raise AttributeError("unreadable attribute")
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        return self.fget(instance)
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    def __set__(self, instance, value):
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        if self.fset is None:
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            raise AttributeError("can't set attribute")
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        self.fset(instance, value)
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    def __delete__(self, instance):
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        if self.fdel is None:
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            raise AttributeError("can't delete attribute")
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        self.fdel(instance)
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    def getter(self, fget):
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        fdoc = fget.__doc__ if self.overwrite_doc else None
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        result = type(self)(fget, self.fset, self.fdel, fdoc or self.__doc__)
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        result.overwrite_doc = self.overwrite_doc
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        return result
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    def setter(self, fset):
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        result = type(self)(self.fget, fset, self.fdel, self.__doc__)
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        result.overwrite_doc = self.overwrite_doc
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        return result
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    def deleter(self, fdel):
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        result = type(self)(self.fget, self.fset, fdel, self.__doc__)
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        result.overwrite_doc = self.overwrite_doc
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        return result
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class _GeneratorWrapper:
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    # TODO: Implement this in C.
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    def __init__(self, gen):
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        self.__wrapped = gen
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        self.__isgen = gen.__class__ is GeneratorType
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        self.__name__ = getattr(gen, '__name__', None)
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        self.__qualname__ = getattr(gen, '__qualname__', None)
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    def send(self, val):
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        return self.__wrapped.send(val)
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    def throw(self, tp, *rest):
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        return self.__wrapped.throw(tp, *rest)
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    def close(self):
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        return self.__wrapped.close()
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    @property
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    def gi_code(self):
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        return self.__wrapped.gi_code
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    @property
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    def gi_frame(self):
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        return self.__wrapped.gi_frame
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    @property
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    def gi_running(self):
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        return self.__wrapped.gi_running
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    @property
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    def gi_yieldfrom(self):
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        return self.__wrapped.gi_yieldfrom
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    cr_code = gi_code
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    cr_frame = gi_frame
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    cr_running = gi_running
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    cr_await = gi_yieldfrom
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    def __next__(self):
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        return next(self.__wrapped)
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    def __iter__(self):
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        if self.__isgen:
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            return self.__wrapped
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        return self
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    __await__ = __iter__
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def coroutine(func):
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    """Convert regular generator function to a coroutine."""
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    if not callable(func):
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        raise TypeError('types.coroutine() expects a callable')
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    if (func.__class__ is FunctionType and
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        getattr(func, '__code__', None).__class__ is CodeType):
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        co_flags = func.__code__.co_flags
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        # Check if 'func' is a coroutine function.
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        # (0x180 == CO_COROUTINE | CO_ITERABLE_COROUTINE)
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        if co_flags & 0x180:
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            return func
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        # Check if 'func' is a generator function.
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        # (0x20 == CO_GENERATOR)
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        if co_flags & 0x20:
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            # TODO: Implement this in C.
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            co = func.__code__
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            # 0x100 == CO_ITERABLE_COROUTINE
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            func.__code__ = co.replace(co_flags=co.co_flags | 0x100)
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            return func
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    # The following code is primarily to support functions that
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    # return generator-like objects (for instance generators
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    # compiled with Cython).
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    # Delay functools and _collections_abc import for speeding up types import.
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    import functools
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    import _collections_abc
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    @functools.wraps(func)
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    def wrapped(*args, **kwargs):
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        coro = func(*args, **kwargs)
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        if (coro.__class__ is CoroutineType or
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            coro.__class__ is GeneratorType and coro.gi_code.co_flags & 0x100):
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            # 'coro' is a native coroutine object or an iterable coroutine
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            return coro
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        if (isinstance(coro, _collections_abc.Generator) and
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            not isinstance(coro, _collections_abc.Coroutine)):
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            # 'coro' is either a pure Python generator iterator, or it
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            # implements collections.abc.Generator (and does not implement
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            # collections.abc.Coroutine).
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            return _GeneratorWrapper(coro)
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        # 'coro' is either an instance of collections.abc.Coroutine or
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        # some other object -- pass it through.
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        return coro
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    return wrapped
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GenericAlias = type(list[int])
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Union = type(int | str)
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EllipsisType = type(Ellipsis)
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NoneType = type(None)
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NotImplementedType = type(NotImplemented)
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__all__ = [n for n in globals() if n[:1] != '_']
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