from datetime import datetime, timedelta, timezone
from sqlalchemy.ext.asyncio import AsyncSession
from sqlalchemy import select, func, and_
from app.models.pricing import ElectricityPricing, PricingPeriod
from app.models.energy import EnergyData, EnergyDailySummary
from app.models.device import Device


async def get_active_pricing(db: AsyncSession, energy_type: str = "electricity", date: datetime | None = None):
    """获取当前生效的电价配置"""
    q = select(ElectricityPricing).where(
        and_(
            ElectricityPricing.energy_type == energy_type,
            ElectricityPricing.is_active == True,
        )
    )
    if date:
        q = q.where(
            and_(
                (ElectricityPricing.effective_from == None) | (ElectricityPricing.effective_from <= date),
                (ElectricityPricing.effective_to == None) | (ElectricityPricing.effective_to >= date),
            )
        )
    q = q.order_by(ElectricityPricing.created_at.desc()).limit(1)
    result = await db.execute(q)
    return result.scalar_one_or_none()


async def get_pricing_periods(db: AsyncSession, pricing_id: int, month: int | None = None):
    """获取电价时段配置"""
    q = select(PricingPeriod).where(PricingPeriod.pricing_id == pricing_id)
    result = await db.execute(q)
    periods = result.scalars().all()
    if month is not None:
        periods = [p for p in periods if p.applicable_months is None or month in p.applicable_months]
    return periods


def get_period_for_hour(periods: list, hour: int) -> PricingPeriod | None:
    """根据小时确定所属时段"""
    hour_str = f"{hour:02d}:00"
    for p in periods:
        start = p.start_time
        end = p.end_time
        if start <= end:
            if start <= hour_str < end:
                return p
        else:  # crosses midnight, e.g. 23:00 - 07:00
            if hour_str >= start or hour_str < end:
                return p
    return periods[0] if periods else None


async def calculate_daily_cost(db: AsyncSession, date: datetime, device_id: int | None = None):
    """计算某天的用电费用"""
    pricing = await get_active_pricing(db, "electricity", date)
    if not pricing:
        return 0.0

    if pricing.pricing_type == "flat":
        # 平价: 直接查日汇总
        q = select(func.sum(EnergyDailySummary.total_consumption)).where(
            and_(
                EnergyDailySummary.date >= date.replace(hour=0, minute=0, second=0),
                EnergyDailySummary.date < date.replace(hour=0, minute=0, second=0) + timedelta(days=1),
                EnergyDailySummary.energy_type == "electricity",
            )
        )
        if device_id:
            q = q.where(EnergyDailySummary.device_id == device_id)
        result = await db.execute(q)
        total_energy = result.scalar() or 0.0

        periods = await get_pricing_periods(db, pricing.id)
        flat_price = periods[0].price_per_unit if periods else 0.0
        cost = total_energy * flat_price
    else:
        # TOU分时: 按小时计算
        periods = await get_pricing_periods(db, pricing.id, month=date.month)
        if not periods:
            return 0.0

        cost = 0.0
        day_start = date.replace(hour=0, minute=0, second=0, microsecond=0)
        for hour in range(24):
            hour_start = day_start + timedelta(hours=hour)
            hour_end = hour_start + timedelta(hours=1)

            q = select(func.sum(EnergyData.value)).where(
                and_(
                    EnergyData.timestamp >= hour_start,
                    EnergyData.timestamp < hour_end,
                    EnergyData.data_type == "energy",
                )
            )
            if device_id:
                q = q.where(EnergyData.device_id == device_id)
            result = await db.execute(q)
            hour_energy = result.scalar() or 0.0

            period = get_period_for_hour(periods, hour)
            if period:
                cost += hour_energy * period.price_per_unit

    # Update daily summary cost
    q = select(EnergyDailySummary).where(
        and_(
            EnergyDailySummary.date >= date.replace(hour=0, minute=0, second=0),
            EnergyDailySummary.date < date.replace(hour=0, minute=0, second=0) + timedelta(days=1),
            EnergyDailySummary.energy_type == "electricity",
        )
    )
    if device_id:
        q = q.where(EnergyDailySummary.device_id == device_id)
    result = await db.execute(q)
    for summary in result.scalars().all():
        summary.cost = cost

    return round(cost, 2)


async def get_cost_summary(
    db: AsyncSession, start_date: datetime, end_date: datetime,
    group_by: str = "day", energy_type: str = "electricity",
):
    """获取费用汇总"""
    q = select(
        EnergyDailySummary.date,
        func.sum(EnergyDailySummary.total_consumption).label("consumption"),
        func.sum(EnergyDailySummary.cost).label("cost"),
    ).where(
        and_(
            EnergyDailySummary.date >= start_date,
            EnergyDailySummary.date <= end_date,
            EnergyDailySummary.energy_type == energy_type,
        )
    )

    if group_by == "device":
        q = select(
            EnergyDailySummary.device_id,
            Device.name.label("device_name"),
            func.sum(EnergyDailySummary.total_consumption).label("consumption"),
            func.sum(EnergyDailySummary.cost).label("cost"),
        ).join(Device, EnergyDailySummary.device_id == Device.id, isouter=True).where(
            and_(
                EnergyDailySummary.date >= start_date,
                EnergyDailySummary.date <= end_date,
                EnergyDailySummary.energy_type == energy_type,
            )
        ).group_by(EnergyDailySummary.device_id, Device.name)
        result = await db.execute(q)
        return [
            {"device_id": r[0], "device_name": r[1] or f"Device#{r[0]}",
             "consumption": round(r[2] or 0, 2), "cost": round(r[3] or 0, 2)}
            for r in result.all()
        ]
    elif group_by == "month":
        from app.core.config import get_settings
        settings = get_settings()
        if settings.is_sqlite:
            group_expr = func.strftime('%Y-%m', EnergyDailySummary.date).label('period')
        else:
            group_expr = func.to_char(EnergyDailySummary.date, 'YYYY-MM').label('period')
        q = select(
            group_expr,
            func.sum(EnergyDailySummary.total_consumption).label("consumption"),
            func.sum(EnergyDailySummary.cost).label("cost"),
        ).where(
            and_(
                EnergyDailySummary.date >= start_date,
                EnergyDailySummary.date <= end_date,
                EnergyDailySummary.energy_type == energy_type,
            )
        ).group_by(group_expr).order_by(group_expr)
        result = await db.execute(q)
        return [
            {"period": str(r[0]), "consumption": round(r[1] or 0, 2), "cost": round(r[2] or 0, 2)}
            for r in result.all()
        ]
    else:  # day
        q = q.group_by(EnergyDailySummary.date).order_by(EnergyDailySummary.date)
        result = await db.execute(q)
        return [
            {"date": str(r[0]), "consumption": round(r[1] or 0, 2), "cost": round(r[2] or 0, 2)}
            for r in result.all()
        ]


async def get_cost_breakdown(db: AsyncSession, start_date: datetime, end_date: datetime, energy_type: str = "electricity"):
    """获取峰谷平费用分布"""
    pricing = await get_active_pricing(db, energy_type, start_date)
    if not pricing:
        return {"periods": [], "total_cost": 0, "total_consumption": 0}

    periods = await get_pricing_periods(db, pricing.id)
    if not periods:
        return {"periods": [], "total_cost": 0, "total_consumption": 0}

    # For each period, calculate the total energy consumption in those hours
    breakdown = []
    total_cost = 0.0
    total_consumption = 0.0

    for period in periods:
        start_hour = int(period.start_time.split(":")[0])
        end_hour = int(period.end_time.split(":")[0])

        if start_hour < end_hour:
            hours = list(range(start_hour, end_hour))
        else:  # crosses midnight
            hours = list(range(start_hour, 24)) + list(range(0, end_hour))

        period_energy = 0.0
        current = start_date.replace(hour=0, minute=0, second=0, microsecond=0)
        end = end_date.replace(hour=23, minute=59, second=59, microsecond=0)

        # Sum energy for all matching hours in date range using daily summary approximation
        q = select(func.sum(EnergyDailySummary.total_consumption)).where(
            and_(
                EnergyDailySummary.date >= start_date,
                EnergyDailySummary.date <= end_date,
                EnergyDailySummary.energy_type == energy_type,
            )
        )
        result = await db.execute(q)
        total_daily = result.scalar() or 0.0

        # Approximate proportion based on hours in period vs 24h
        proportion = len(hours) / 24.0
        period_energy = total_daily * proportion
        period_cost = period_energy * period.price_per_unit

        total_cost += period_cost
        total_consumption += period_energy

        period_name_map = {
            "peak": "尖峰", "sharp": "尖峰",
            "high": "高峰", "shoulder": "高峰",
            "flat": "平段",
            "valley": "低谷", "off_peak": "低谷",
        }

        breakdown.append({
            "period_name": period.period_name,
            "period_label": period_name_map.get(period.period_name, period.period_name),
            "start_time": period.start_time,
            "end_time": period.end_time,
            "price_per_unit": period.price_per_unit,
            "consumption": round(period_energy, 2),
            "cost": round(period_cost, 2),
            "proportion": round(proportion * 100, 1),
        })

    return {
        "periods": breakdown,
        "total_cost": round(total_cost, 2),
        "total_consumption": round(total_consumption, 2),
        "pricing_name": pricing.name,
        "pricing_type": pricing.pricing_type,
    }