def __new__()

in antlir/shape.py [0:0]

• 15 lines of code
• 9 McCabe index (conditional complexity)

    def __new__(metacls, name, bases, dct):  # noqa: B902
        cls = super().__new__(metacls, name, bases, dct)
        # Only apply shape meta hacks to generated classes, not user-written
        # subclasses
        cls.__GENERATED_SHAPE__ = dct.get("__GENERATED_SHAPE__", False)
        if cls.__GENERATED_SHAPE__:
            cls.__name__ = repr(cls)
            cls.__qualname__ = repr(cls)

            # create an inner class `types` to make all the fields types usable
            # from a user of shape without having to know the cryptic generated
            # class names
            if "types" in dct or "types" in dct.get("__annotations__", {}):
                raise KeyError("'types' cannot be used as a shape field name")
            types_cls = {}
            for key, f in cls.__fields__.items():
                types_cls[key] = f.type_
                # pydantic already does some magic to extract list element
                # types and dict value types, but export tuples as a tuple of
                # types instead of typing.Tuple
                # NOTE: pydantic extracts the dict value type as the type,
                # which is a little bit of a strange interface, so that is
                # liable to change if we ever care about making a dict key
                # accessible (for example, if the key is a shape)
                if getattr(f.type_, "__origin__", None) == tuple:
                    types_cls[key] = f.type_.__args__
            cls.types = type("types", (object,), types_cls)

        return cls