"""推荐列表 API"""

from fastapi import APIRouter

from app.engine.recommender import (
    refresh_recommendations,
    get_latest_recommendations,
    get_recommendation_history,
    get_performance_stats,
)
from app.config import is_trading_hours

router = APIRouter(prefix="/api/recommendations", tags=["recommendations"])


@router.get("/latest")
async def get_latest():
    """获取最新推荐列表"""
    result = await get_latest_recommendations()

    mt = result.get("market_temp")
    return {
        "market_temperature": {
            "trade_date": mt.trade_date if mt else "",
            "temperature": mt.temperature if mt else 0,
            "up_count": mt.up_count if mt else 0,
            "down_count": mt.down_count if mt else 0,
            "limit_up_count": mt.limit_up_count if mt else 0,
            "limit_down_count": mt.limit_down_count if mt else 0,
            "max_streak": mt.max_streak if mt else 0,
            "broken_rate": mt.broken_rate if mt else 0,
            "index_above_ma20": mt.index_above_ma20 if mt else False,
        } if mt else None,
        "recommendations": [
            {
                "ts_code": r.ts_code,
                "name": r.name,
                "sector": r.sector,
                "score": r.score,
                "level": r.level,
                "signal": r.signal,
                "market_temp_score": r.market_temp_score,
                "sector_score": r.sector_score,
                "capital_score": r.capital_score,
                "technical_score": r.technical_score,
                "supply_demand_score": r.supply_demand_score,
                "price_action_score": r.price_action_score,
                "position_score": r.position_score,
                "valuation_score": r.valuation_score,
                "entry_price": r.entry_price,
                "target_price": r.target_price,
                "stop_loss": r.stop_loss,
                "reasons": r.reasons,
                "risk_note": r.risk_note,
                "llm_analysis": r.llm_analysis,
                "entry_timing": r.entry_timing,
                "llm_score": r.llm_score,
                "strategy": r.strategy,
                "entry_signal_type": r.entry_signal_type,
                "scan_session": r.scan_session,
                "created_at": r.created_at.isoformat() if r.created_at else None,
            }
            for r in result.get("recommendations", [])
        ],
        "scan_mode": result.get("scan_mode", "unknown"),
    }


@router.post("/refresh")
async def refresh(scan_session: str = "manual"):
    """手动触发一次全量筛选"""
    result = await refresh_recommendations(scan_session=scan_session)
    rec_count = len(result.get("recommendations", []))
    mt = result.get("market_temp")
    return {
        "status": "ok",
        "count": rec_count,
        "temperature": mt.temperature if mt else 0,
        "scan_mode": result.get("scan_mode", "unknown"),
        "is_trading": is_trading_hours(),
    }


@router.post("/update-tracking")
async def update_tracking():
    """独立更新推荐跟踪数据（不触发新扫描，盘中可单独调用）"""
    from app.engine.recommender import _update_tracking
    await _update_tracking()
    stats = await get_performance_stats()
    return {
        "status": "ok",
        "tracked": stats.get("tracked", 0),
        "win_rate": stats.get("win_rate", 0),
        "avg_return": stats.get("avg_return", 0),
    }


@router.get("/status")
async def get_scan_status():
    """获取当前扫描状态信息"""
    return {
        "is_trading": is_trading_hours(),
        "scan_mode": "intraday" if is_trading_hours() else "post_market",
        "description": "盘中实时扫描（腾讯行情）" if is_trading_hours() else "盘后分析（Tushare日级数据）",
    }


@router.get("/history")
async def get_history(days: int = 7):
    """获取历史推荐（按日期分组）"""
    return await get_recommendation_history(days)


@router.get("/performance")
async def performance():
    """获取推荐胜率统计"""
    return await get_performance_stats()