"""Minimal NovaPlan DSL scaffolding.

This module provides lightweight dataclasses to model a canonical signal/plan
DSL that can be used by adapters and bridge components to represent local
problems, signals, and planning hypotheses in a structured way.

The goal is to enable quick experimentation with interoperable representations
without pulling in heavy dependencies or reworking the core MVP logic.
"""
from __future__ import annotations

import json
from dataclasses import dataclass, asdict
from typing import List, Dict, Any


@dataclass
class SignalNode:
    id: str
    metadata: Dict[str, Any]  # arbitrary per-signal metadata (venue, ts, confidence, etc.)

    def to_json(self) -> str:
        return json.dumps(asdict(self))


@dataclass
class Edge:
    src: str
    dst: str
    weight: float = 1.0

    def to_json(self) -> str:
        return json.dumps(asdict(self))


@dataclass
class Scenario:
    name: str
    nodes: List[SignalNode]
    edges: List[Edge]

    def to_json(self) -> str:
        data = {
            "name": self.name,
            "nodes": [asdict(n) for n in self.nodes],
            "edges": [asdict(e) for e in self.edges],
        }
        return json.dumps(data)


@dataclass
class HedgePlan:
    plan_id: str
    scenario: Scenario
    metadata: Dict[str, Any]  # additional plan-level metadata
    timestamp: float

    def to_json(self) -> str:
        data = {
            "plan_id": self.plan_id,
            "scenario": json.loads(self.scenario.to_json()),
            "metadata": self.metadata,
            "timestamp": self.timestamp,
        }
        return json.dumps(data)


__all__ = ["SignalNode", "Edge", "Scenario", "HedgePlan"]