Currently (as implemented in #17414), timetables are serialised by their classes’ full import path. This works most of the time, but not in some cases, including:

* Nested in class or function
* Declared directly in a DAG file without a valid import name (e.g. `12345.py`)

It’s fundamentally impossible to fix some of the cases (e.g. function-local class declaration) due to how Python works, but by requiring the user to explicitly register the timetable class, we can at least expose that problem so users don’t attempt to do that.

However, since the timetable actually would work a lot of times without any additional mechanism, I’m also wondering if we should _require_ registration.

1. Always require registration. A DAG using an unregistered timetable class fails to serialise.
2. Only require registration when the timetable class has wonky import path. “Normal” classes work out of the box without registering, and user sees a serialisation error asking for registration otherwise.
3. Don’t require registration. If a class cannot be correctly serialised, tell the user we can’t do it and the timetable must be declared another way.
airflow/serialization/serialized_objects.py
"""Encode a timetable instance.
    This delegates most of the serialization work to the type, so the behavior
    can be completely controlled by a custom subclass.
    """
    return {"type": as_importable_string(type(var)), "value": var.serialize()}
def decode_timetable(var: Dict[str, Any]) -> Timetable:
    """Decode a previously serialized timetable.
    Most of the deserialization logic is delegated to the actual type, which
    we import from string.
    """
    return import_string(var["type"]).deserialize(var["value"])
class BaseSerialization:
    """BaseSerialization provides utils for serialization."""
    
    _primitive_types = (int, bool, float, str)
    
    
    _datetime_types = (datetime.datetime,)
    
    _excluded_types = (logging.Logger, Connection, type)
    _json_schema: Optional[Validator] = None
    
    
    
    _load_operator_extra_links = True
    _CONSTRUCTOR_PARAMS: Dict[str, Parameter] = {}
    SERIALIZER_VERSION = 1
    @classmethod
    def to_json(cls, var: Union[DAG, BaseOperator, dict, list, set, tuple]) -> str: