from __future__ import annotations

import asyncio
import time
import uuid
from dataclasses import dataclass, field
from typing import Dict, Any

from .models import LocalRobotPlan, PlanDelta, SharedSignals, DualVariables

# Simple, production-leaning delta version counter to enable deterministic repro and auditing
_delta_version: int = 0


@dataclass
class SolverState:
    duals: Dict[str, DualVariables] = field(default_factory=dict)
    deltas: Dict[str, PlanDelta] = field(default_factory=dict)


async def admm_step(left_plan: LocalRobotPlan, right_plan: LocalRobotPlan, signals: SharedSignals) -> PlanDelta:
    # Very small, toy ADMM-like step: adjust a simple objective value per fleet and produce delta
    # This is a placeholder for a real, more complex asynchronous coordination loop.
    await asyncio.sleep(0.01)  # simulate async work
    delta_changes = {
        "cost_improvement": max(0.0, 1.0 - signals.signals.get("energy", 0.0))
    }
    # Increment a global delta version for deterministic reconciliation/auditing
    global _delta_version
    _delta_version += 1
    nonce = uuid.uuid4().hex
    timestamp = time.time()
    return PlanDelta(
        delta_id=f"delta-{left_plan.robot_id}-{right_plan.robot_id}",
        fleet_id=left_plan.fleet_id,
        changes=delta_changes,
        version=_delta_version,
        nonce=nonce,
        timestamp=timestamp,
    )


async def coordinate_fleets(left_plan: LocalRobotPlan, right_plan: LocalRobotPlan, registry_signals: SharedSignals) -> PlanDelta:
    # Run a single ADMM-like step between two fleets.
    delta = await admm_step(left_plan, right_plan, registry_signals)
    return delta