"""核心股历史接口：活跃核心股 + 指定日核心股/题材前20"""

from datetime import date as date_cls

from fastapi import APIRouter, Query
from fastapi.responses import JSONResponse
from database import get_connection, dict_from_row

router = APIRouter()

_NO_CACHE_HEADERS = {"Cache-Control": "no-store, no-cache, must-revalidate, max-age=0"}


def _recent_trade_dates(conn, n: int = 10) -> list[str]:
    """最近 n 个有数据的交易日（升序）"""
    rows = conn.execute(
        "SELECT DISTINCT trade_date FROM daily_core_stocks ORDER BY trade_date DESC LIMIT ?",
        (n,),
    ).fetchall()
    return [r["trade_date"] for r in reversed(rows)]


@router.get("/active", summary="活跃核心股 + 最近10日涨幅矩阵")
async def active_core_stocks():
    conn = get_connection()
    try:
        dates = _recent_trade_dates(conn, 10)
        if not dates:
            return JSONResponse({"dates": [], "stocks": []}, headers=_NO_CACHE_HEADERS)

        # 窗口内出现过且最近一次出现距今天数 <= 10 个交易日
        placeholders = ",".join("?" * len(dates))
        rows = conn.execute(
            f"""SELECT trade_date, stock_code, stock_name, f3, cover_count FROM daily_core_stocks
                WHERE trade_date IN ({placeholders})
                ORDER BY trade_date DESC, rank ASC""",
            dates,
        ).fetchall()

        # 组装 per-stock:每日涨幅 + 出现次数 + 最近上榜
        stock_days: dict[str, dict] = {}
        for r in rows:
            code = r["stock_code"]
            s = stock_days.setdefault(code, {
                "stockCode": code,
                "stockName": r["stock_name"],
                "coverCount": r["cover_count"],
                "dailyGains": {},
                "appearCount": 0,
                "lastAppear": None,
            })
            s["dailyGains"][r["trade_date"]] = r["f3"]
            s["appearCount"] += 1
            if s["lastAppear"] is None or r["trade_date"] > s["lastAppear"]:
                s["lastAppear"] = r["trade_date"]

        stocks = list(stock_days.values())
        # 稳定排序：先按出现次数降序，再按最近上榜日降序
        stocks.sort(key=lambda x: x.get("lastAppear") or "", reverse=True)
        stocks.sort(key=lambda x: -x["appearCount"])

        # daysSinceLastAppear:最近上榜距窗口最新交易日的自然日差(简单口径)
        latest = dates[-1] if dates else None
        for s in stocks:
            if s.get("lastAppear") and latest:
                try:
                    d1 = date_cls.fromisoformat(latest)
                    d2 = date_cls.fromisoformat(s["lastAppear"])
                    s["daysSinceLastAppear"] = (d1 - d2).days
                except ValueError:
                    s["daysSinceLastAppear"] = 0
            else:
                s["daysSinceLastAppear"] = 0

        return JSONResponse({"dates": dates, "stocks": stocks}, headers=_NO_CACHE_HEADERS)
    finally:
        conn.close()


@router.get("/history", summary="指定交易日核心股(含所属题材)")
async def core_stock_history(date: str = Query(..., description="交易日 YYYY-MM-DD")):
    conn = get_connection()
    try:
        rows = conn.execute(
            "SELECT * FROM daily_core_stocks WHERE trade_date = ? ORDER BY rank ASC", (date,)
        ).fetchall()
        # 一次性取该日全部题材关联，按 stock_code 分组，避免逐股 N+1 查询
        themes_rows = conn.execute(
            "SELECT stock_code, theme_code, theme_name FROM daily_core_stock_themes WHERE trade_date = ?",
            (date,),
        ).fetchall()
        themes_by_stock: dict[str, list] = {}
        for t in themes_rows:
            themes_by_stock.setdefault(t["stock_code"], []).append(
                {"theme_code": t["theme_code"], "theme_name": t["theme_name"]}
            )
        items = []
        for r in rows:
            d = dict_from_row(r)
            d["themes"] = themes_by_stock.get(d["stock_code"], [])
            items.append(d)
        return JSONResponse({"date": date, "items": items}, headers=_NO_CACHE_HEADERS)
    finally:
        conn.close()