296 lines
9.7 KiB
Python
296 lines
9.7 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 _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 (see Enum for an example).
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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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func.__code__ = CodeType(
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co.co_argcount, co.co_kwonlyargcount, co.co_nlocals,
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co.co_stacksize,
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co.co_flags | 0x100, # 0x100 == CO_ITERABLE_COROUTINE
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co.co_code,
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co.co_consts, co.co_names, co.co_varnames, co.co_filename,
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co.co_name, co.co_firstlineno, co.co_lnotab, co.co_freevars,
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co.co_cellvars)
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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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__all__ = [n for n in globals() if n[:1] != '_']
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