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types.py9.6 KB · 300 lines
"""Define names for built-in types that aren't directly accessible as a builtin."""import sys # Iterators in Python aren't a matter of type but of protocol.  A large# and changing number of builtin types implement *some* flavor of# iterator.  Don't check the type!  Use hasattr to check for both# "__iter__" and "__next__" attributes instead. def _f(): passFunctionType = type(_f)LambdaType = type(lambda: None)         # Same as FunctionTypeCodeType = type(_f.__code__)MappingProxyType = type(type.__dict__)SimpleNamespace = type(sys.implementation) def _cell_factory():    a = 1    def f():        nonlocal a    return f.__closure__[0]CellType = type(_cell_factory()) def _g():    yield 1GeneratorType = type(_g()) async def _c(): pass_c = _c()CoroutineType = type(_c)_c.close()  # Prevent ResourceWarning async def _ag():    yield_ag = _ag()AsyncGeneratorType = type(_ag) class _C:    def _m(self): passMethodType = type(_C()._m) BuiltinFunctionType = type(len)BuiltinMethodType = type([].append)     # Same as BuiltinFunctionType WrapperDescriptorType = type(object.__init__)MethodWrapperType = type(object().__str__)MethodDescriptorType = type(str.join)ClassMethodDescriptorType = type(dict.__dict__['fromkeys']) ModuleType = type(sys) try:    raise TypeErrorexcept TypeError:    tb = sys.exc_info()[2]    TracebackType = type(tb)    FrameType = type(tb.tb_frame)    tb = None; del tb # For Jython, the following two types are identicalGetSetDescriptorType = type(FunctionType.__code__)MemberDescriptorType = type(FunctionType.__globals__) del sys, _f, _g, _C, _c, _ag  # Not for export  # Provide a PEP 3115 compliant mechanism for class creationdef new_class(name, bases=(), kwds=None, exec_body=None):    """Create a class object dynamically using the appropriate metaclass."""    resolved_bases = resolve_bases(bases)    meta, ns, kwds = prepare_class(name, resolved_bases, kwds)    if exec_body is not None:        exec_body(ns)    if resolved_bases is not bases:        ns['__orig_bases__'] = bases    return meta(name, resolved_bases, ns, **kwds) def resolve_bases(bases):    """Resolve MRO entries dynamically as specified by PEP 560."""    new_bases = list(bases)    updated = False    shift = 0    for i, base in enumerate(bases):        if isinstance(base, type) and not isinstance(base, GenericAlias):            continue        if not hasattr(base, "__mro_entries__"):            continue        new_base = base.__mro_entries__(bases)        updated = True        if not isinstance(new_base, tuple):            raise TypeError("__mro_entries__ must return a tuple")        else:            new_bases[i+shift:i+shift+1] = new_base            shift += len(new_base) - 1    if not updated:        return bases    return tuple(new_bases) def prepare_class(name, bases=(), kwds=None):    """Call the __prepare__ method of the appropriate metaclass.     Returns (metaclass, namespace, kwds) as a 3-tuple     *metaclass* is the appropriate metaclass    *namespace* is the prepared class namespace    *kwds* is an updated copy of the passed in kwds argument with any    'metaclass' entry removed. If no kwds argument is passed in, this will    be an empty dict.    """    if kwds is None:        kwds = {}    else:        kwds = dict(kwds) # Don't alter the provided mapping    if 'metaclass' in kwds:        meta = kwds.pop('metaclass')    else:        if bases:            meta = type(bases[0])        else:            meta = type    if isinstance(meta, type):        # when meta is a type, we first determine the most-derived metaclass        # instead of invoking the initial candidate directly        meta = _calculate_meta(meta, bases)    if hasattr(meta, '__prepare__'):        ns = meta.__prepare__(name, bases, **kwds)    else:        ns = {}    return meta, ns, kwds def _calculate_meta(meta, bases):    """Calculate the most derived metaclass."""    winner = meta    for base in bases:        base_meta = type(base)        if issubclass(winner, base_meta):            continue        if issubclass(base_meta, winner):            winner = base_meta            continue        # else:        raise TypeError("metaclass conflict: "                        "the metaclass of a derived class "                        "must be a (non-strict) subclass "                        "of the metaclasses of all its bases")    return winner class DynamicClassAttribute:    """Route attribute access on a class to __getattr__.     This is a descriptor, used to define attributes that act differently when    accessed through an instance and through a class.  Instance access remains    normal, but access to an attribute through a class will be routed to the    class's __getattr__ method; this is done by raising AttributeError.     This allows one to have properties active on an instance, and have virtual    attributes on the class with the same name (see Enum for an example).     """    def __init__(self, fget=None, fset=None, fdel=None, doc=None):        self.fget = fget        self.fset = fset        self.fdel = fdel        # next two lines make DynamicClassAttribute act the same as property        self.__doc__ = doc or fget.__doc__        self.overwrite_doc = doc is None        # support for abstract methods        self.__isabstractmethod__ = bool(getattr(fget, '__isabstractmethod__', False))     def __get__(self, instance, ownerclass=None):        if instance is None:            if self.__isabstractmethod__:                return self            raise AttributeError()        elif self.fget is None:            raise AttributeError("unreadable attribute")        return self.fget(instance)     def __set__(self, instance, value):        if self.fset is None:            raise AttributeError("can't set attribute")        self.fset(instance, value)     def __delete__(self, instance):        if self.fdel is None:            raise AttributeError("can't delete attribute")        self.fdel(instance)     def getter(self, fget):        fdoc = fget.__doc__ if self.overwrite_doc else None        result = type(self)(fget, self.fset, self.fdel, fdoc or self.__doc__)        result.overwrite_doc = self.overwrite_doc        return result     def setter(self, fset):        result = type(self)(self.fget, fset, self.fdel, self.__doc__)        result.overwrite_doc = self.overwrite_doc        return result     def deleter(self, fdel):        result = type(self)(self.fget, self.fset, fdel, self.__doc__)        result.overwrite_doc = self.overwrite_doc        return result  class _GeneratorWrapper:    # TODO: Implement this in C.    def __init__(self, gen):        self.__wrapped = gen        self.__isgen = gen.__class__ is GeneratorType        self.__name__ = getattr(gen, '__name__', None)        self.__qualname__ = getattr(gen, '__qualname__', None)    def send(self, val):        return self.__wrapped.send(val)    def throw(self, tp, *rest):        return self.__wrapped.throw(tp, *rest)    def close(self):        return self.__wrapped.close()    @property    def gi_code(self):        return self.__wrapped.gi_code    @property    def gi_frame(self):        return self.__wrapped.gi_frame    @property    def gi_running(self):        return self.__wrapped.gi_running    @property    def gi_yieldfrom(self):        return self.__wrapped.gi_yieldfrom    cr_code = gi_code    cr_frame = gi_frame    cr_running = gi_running    cr_await = gi_yieldfrom    def __next__(self):        return next(self.__wrapped)    def __iter__(self):        if self.__isgen:            return self.__wrapped        return self    __await__ = __iter__ def coroutine(func):    """Convert regular generator function to a coroutine."""     if not callable(func):        raise TypeError('types.coroutine() expects a callable')     if (func.__class__ is FunctionType and        getattr(func, '__code__', None).__class__ is CodeType):         co_flags = func.__code__.co_flags         # Check if 'func' is a coroutine function.        # (0x180 == CO_COROUTINE | CO_ITERABLE_COROUTINE)        if co_flags & 0x180:            return func         # Check if 'func' is a generator function.        # (0x20 == CO_GENERATOR)        if co_flags & 0x20:            # TODO: Implement this in C.            co = func.__code__            # 0x100 == CO_ITERABLE_COROUTINE            func.__code__ = co.replace(co_flags=co.co_flags | 0x100)            return func     # The following code is primarily to support functions that    # return generator-like objects (for instance generators    # compiled with Cython).     # Delay functools and _collections_abc import for speeding up types import.    import functools    import _collections_abc    @functools.wraps(func)    def wrapped(*args, **kwargs):        coro = func(*args, **kwargs)        if (coro.__class__ is CoroutineType or            coro.__class__ is GeneratorType and coro.gi_code.co_flags & 0x100):            # 'coro' is a native coroutine object or an iterable coroutine            return coro        if (isinstance(coro, _collections_abc.Generator) and            not isinstance(coro, _collections_abc.Coroutine)):            # 'coro' is either a pure Python generator iterator, or it            # implements collections.abc.Generator (and does not implement            # collections.abc.Coroutine).            return _GeneratorWrapper(coro)        # 'coro' is either an instance of collections.abc.Coroutine or        # some other object -- pass it through.        return coro     return wrapped  GenericAlias = type(list[int])  __all__ = [n for n in globals() if n[:1] != '_']