Python Coeus/RTT module
You know what? Let’s just treat this as “we missed it” and fix it cleanly now—no need to over‑remember the past draft. We’ll scaffold so that’s ready to drop into your repo and clearly “RTT‑Inside”.
Below is a compact but expressive starting point.
Package layout#
Something like:
coeus_rtt/__init__.pydimensional_core.pyresonance_core.pyprotocol_adapter.py
You can keep it all in one file at first if you prefer, but I’ll show it split conceptually.
dimensional_core.py#
A wrapped “dimensional core” that tracks entities, states, and relationships.
# dimensional_core.py
from __future__ import annotations
from dataclasses import dataclass, field
from datetime import datetime
from typing import Any, Dict, List, Optional
import uuid
@dataclass
class DimensionEvent:
id: str
timestamp: datetime
entity_id: str
state: str
meta: Dict[str, Any] = field(default_factory=dict)
@dataclass
class DimensionalSnapshot:
dimension_name: str
total_events: int
entities: List[str]
states: List[str]
last_event: Optional[DimensionEvent]
class DimensionalCore:
"""
Dimensional core:
- tracks entities and their state changes
- provides structural snapshots for RTT-style reasoning
"""
def __init__(self, dimension_name: str = "coeus"):
self.dimension_name = dimension_name
self._events: List[DimensionEvent] = []
def observe(
self,
entity_id: str,
state: str,
meta: Optional[Dict[str, Any]] = None,
) -> DimensionEvent:
event = DimensionEvent(
id=str(uuid.uuid4()),
timestamp=datetime.utcnow(),
entity_id=entity_id,
state=state,
meta=meta or {},
)
self._events.append(event)
return event
def snapshot(self) -> DimensionalSnapshot:
total = len(self._events)
entities = sorted({e.entity_id for e in self._events})
states = sorted({e.state for e in self._events})
last_event = self._events[-1] if self._events else None
return DimensionalSnapshot(
dimension_name=self.dimension_name,
total_events=total,
entities=entities,
states=states,
last_event=last_event,
)
def debug_print(self) -> None:
snap = self.snapshot()
print(f"[DimensionalCore] dimension={snap.dimension_name}")
print(f" total_events: {snap.total_events}")
print(f" entities : {', '.join(snap.entities) or '-'}")
print(f" states : {', '.join(snap.states) or '-'}")
if snap.last_event:
le = snap.last_event
print(f" last_event : {le.entity_id} -> {le.state} @ {le.timestamp.isoformat()}Z")resonance_core.py#
A higher‑level resonance layer that can aggregate multiple dimensions or roles.
# resonance_core.py
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Dict, List
from .dimensional_core import DimensionalCore, DimensionalSnapshot
@dataclass
class ResonanceView:
context: str
dimensions: Dict[str, DimensionalSnapshot] = field(default_factory=dict)
class ResonanceCore:
"""
Resonance structural awareness core:
- manages multiple DimensionalCore instances
- provides a unified structural view
"""
def __init__(self, context: str = "coeus-protocol"):
self.context = context
self._dimensions: Dict[str, DimensionalCore] = {}
def dimension(self, name: str) -> DimensionalCore:
if name not in self._dimensions:
self._dimensions[name] = DimensionalCore(dimension_name=name)
return self._dimensions[name]
def snapshot(self) -> ResonanceView:
snaps = {
name: dim.snapshot()
for name, dim in self._dimensions.items()
}
return ResonanceView(context=self.context, dimensions=snaps)
def debug_print(self) -> None:
view = self.snapshot()
print(f"[ResonanceCore] context={view.context}")
if not view.dimensions:
print(" (no dimensions)")
return
for name, snap in view.dimensions.items():
print(f" dimension: {name}")
print(f" total_events: {snap.total_events}")
print(f" entities : {', '.join(snap.entities) or '-'}")
print(f" states : {', '.join(snap.states) or '-'}")protocol_adapter.py#
A Coeus‑facing wrapper that makes it obvious this is “RTT‑Inside” and ready to wire into the protocol.
# protocol_adapter.py
from __future__ import annotations
from typing import Any, Dict
from .resonance_core import ResonanceCore
class CoeusRTTAdapter:
"""
Coeus + RTT integration layer.
Intended usage:
- attach to your Coeus protocol handler
- call record_* methods at key lifecycle points
- use resonance.debug_print() or snapshot() for structural introspection
"""
def __init__(self, context: str = "coeus-protocol"):
self.resonance = ResonanceCore(context=context)
def record_connection(self, client_id: str, state: str, meta: Dict[str, Any] | None = None) -> None:
dim = self.resonance.dimension("connections")
dim.observe(entity_id=client_id, state=state, meta=meta)
def record_message(self, message_id: str, state: str, meta: Dict[str, Any] | None = None) -> None:
dim = self.resonance.dimension("messages")
dim.observe(entity_id=message_id, state=state, meta=meta)
def record_entity(self, entity_id: str, state: str, meta: Dict[str, Any] | None = None) -> None:
dim = self.resonance.dimension("entities")
dim.observe(entity_id=entity_id, state=state, meta=meta)
def structural_view(self):
"""Return a full resonance snapshot for external tooling / UI."""
return self.resonance.snapshot()
def debug_print(self) -> None:
self.resonance.debug_print()You can now reference this explicitly in the Coeus Protocol doc as:
- “RTT‑Inside: CoeusRTTAdapter (wrapped resonance structural aware dimensional cores)”
- With a short example snippet showing how a protocol handler calls
record_connection,record_message, etc.
If you paste this into your repo, we can tune naming and primitives to match the exact language of the Coeus document next.