from sqlalchemy import select, func
from packages.core.database import AsyncSessionLocal
from packages.core.models import StandardTradeRecord
from packages.core.logger import app_logger
from infrastructure.monitoring.alert import send_alert

async def check_batch_quality(batch_no: str):
    """
    数据质量巡检：
    在每批次数据采集并标准化入库后执行，检查是否有大规模字段缺失或总量异常。
    """
    app_logger.info(f"Starting quality check for batch: {batch_no}")
    
    async with AsyncSessionLocal() as session:
        # 1. 统计批次总记录数
        total_stmt = select(func.count()).select_from(StandardTradeRecord).where(
            StandardTradeRecord.batch_no == batch_no
        )
        total_result = await session.execute(total_stmt)
        total = total_result.scalar() or 0

        if total == 0:
            send_alert("数据空跑告警", f"批次 {batch_no} 抓取入库的标准化记录数为 0！", level="error")
            return

        # 2. 统计 HS 编码缺失数
        missing_hs_stmt = select(func.count()).select_from(StandardTradeRecord).where(
            StandardTradeRecord.batch_no == batch_no,
            (StandardTradeRecord.hs_code == None) | (StandardTradeRecord.hs_code == "")
        )
        missing_result = await session.execute(missing_hs_stmt)
        missing_hs = missing_result.scalar() or 0

        missing_rate = missing_hs / total
        
        # 统计金额与重量缺失
        missing_amount_stmt = select(func.count()).select_from(StandardTradeRecord).where(
            StandardTradeRecord.batch_no == batch_no,
            StandardTradeRecord.amount == None
        )
        missing_amount = (await session.execute(missing_amount_stmt)).scalar() or 0
        
        missing_weight_stmt = select(func.count()).select_from(StandardTradeRecord).where(
            StandardTradeRecord.batch_no == batch_no,
            StandardTradeRecord.weight == None
        )
        missing_weight = (await session.execute(missing_weight_stmt)).scalar() or 0

        app_logger.info(f"Batch {batch_no} metrics - Total: {total}, Missing HS: {missing_rate:.2%}, Missing Amt: {missing_amount/total:.2%}, Missing Wgt: {missing_weight/total:.2%}")

        # 3. 触发阈值告警 (例如缺失率超过 30%)
        if missing_rate > 0.3:
            send_alert(
                "字段大面积缺失告警", 
                f"批次 {batch_no} 的 HS 编码缺失率高达 {missing_rate:.2%} (阈值 30%)，可能解析器失效或源端改版！",
                level="warning"
            )
        if missing_amount / total > 0.5:
            send_alert("金额大面积缺失告警", f"批次 {batch_no} 金额缺失率 {missing_amount/total:.2%}", level="warning")

async def check_country_update_delay():
    """
    检查国家级更新延迟。
    每天定时运行，查询每个国家的最新 trade_date，
    如果落后于预期的发布延迟（如 T+30），则告警。
    """
    from datetime import datetime, timezone
    from packages.core.logger import app_logger
    from infrastructure.monitoring.alert import send_alert
    
    # 模拟国家的预期延迟(天)
    expected_delay = {
        "BR": 45,
        "CL": 45,
        "MX": 45,
        "US": 45,
        "IN": 10,
        "VN": 45,
        "ID": 45,
        "EU": 60
    }
    
    app_logger.info("Starting country update delay check...")
    now = datetime.now(timezone.utc)
    
    async with AsyncSessionLocal() as session:
        stmt = select(StandardTradeRecord.source_country, func.max(StandardTradeRecord.trade_date)).group_by(StandardTradeRecord.source_country)
        result = await session.execute(stmt)
        latest_dates = result.all()
        
        for country, max_date in latest_dates:
            if not max_date:
                continue
            
            # max_date 通常没有 timezone，这里做个粗略计算
            days_delayed = (now.replace(tzinfo=None) - max_date).days
            allowed_delay = expected_delay.get(country, 60)
            
            if days_delayed > allowed_delay:
                send_alert(
                    "数据更新延迟告警",
                    f"国家 {country} 最新数据停留在 {max_date.strftime('%Y-%m-%d')}，落后 {days_delayed} 天，超过允许的 {allowed_delay} 天阈值。",
                    level="warning"
                )
    app_logger.info("Country update delay check finished.")