thanks for the message. Gonna be honest, I'm not sure what you mean by cycles. Can you elaborate a bit?

    A = {}
    B = {}
    A["ref"] = B
    B["ref"] = A

Note that

    print A

    {'ref': {'ref': {...}}}

    class BaseMapper(Mapper):

        __type__ = TestType

        score = Integer()
        nest = Nested('NestedMapper')

        __roles__ = {'nested': blacklist('nest')}

    class NestedMapper(Mapper):

        __type__ = TestType

        back = Nested('BaseMapper', role='nested')
        name = String()

    obj2 = TestType(name='test')
    obj = TestType(score=5, nest=obj2)
    obj2.back = obj

    >> BaseMapper(obj=obj).serialize()
    {'nest': {'back': {'score': 5}, 'name': 'test'}, 'score': 5}

One way is to to store a table of objects (as identified by id()) encountered during serialization, indexed by the order you encounter them. If you encounter an object you have already serialized, serialize an index into that table. On deserialization, construct the same kind of table, and deserialize an index with a reference to the same object.

See e.g. AMF for an example format that does this: https://en.wikipedia.org/wiki/Action_Message_Format

    {'nest': {'back': {'score': 5}, 'name': 'test'}, 'score': 5}

(I might be wrong but it seems to me that the act of serialization has simply expanded the cycle one level deep.)

    a = {}
    b = {}
    a["b"] = b
    b["a"] = a

    a == deserialize(serialize(a))