kopia lustrzana https://github.com/micropython/micropython-lib
102 wiersze
3.4 KiB
Python
102 wiersze
3.4 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 = None # TODO: Add better sentinel which can't match anything
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MappingProxyType = None # TODO: Add better sentinel which can't match anything
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SimpleNamespace = None # TODO: Add better sentinel which can't match anything
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def _g():
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yield 1
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GeneratorType = type(_g())
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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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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 = None # TODO: Add better sentinel which can't match anything
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FrameType = None # TODO: Add better sentinel which can't match anything
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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 = None # TODO: Add better sentinel which can't match anything
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MemberDescriptorType = None # TODO: Add better sentinel which can't match anything
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del sys, _f, _g, _C, # 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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meta, ns, kwds = prepare_class(name, bases, kwds)
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if exec_body is not None:
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exec_body(ns)
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return meta(name, bases, ns, **kwds)
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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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