from __future__ import annotations

from abc import ABC, abstractmethod
from typing import Any, Dict

from .models import LocalProblem, PlanDelta


class Adapter(ABC):
    @abstractmethod
    def start(self) -> None:
        pass

    @abstractmethod
    def stop(self) -> None:
        pass


class MarketDataFeedAdapter(Adapter):
    def __init__(self) -> None:
        self.running = False

    def start(self) -> None:
        self.running = True

    def stop(self) -> None:
        self.running = False

    def get_local_problem(self) -> LocalProblem:
        # Seed a tiny LocalProblem from venue data (mocked here)
        problem = LocalProblem(
            id="lp-001",
            neighborhood="Downtown",
            tasks=[{"type": "evacuation", "constraints": {"capacity": 5000}}],
            capacity=5000,
            equity_budget=0.2,
        )
        return problem


class EdgeComputeAdapter(Adapter):
    def __init__(self) -> None:
        self.running = False

    def start(self) -> None:
        self.running = True

    def stop(self) -> None:
        self.running = False

    def process_delta(self, delta: PlanDelta) -> PlanDelta:
        # Minimal processing: append an execution action and bump version
        plan = dict(delta.plan)
        actions = plan.get("actions", [])
        actions.append({"action": "recompute", "at": "edge"})
        plan["actions"] = actions
        new_delta = PlanDelta(version=delta.version + 1, plan=plan, provenance="edge", signature="edge-sig")
        return new_delta