"""AkShare 数据服务层。

每个函数都做了 try/except 降级：真实数据拿不到时返回 Python 端生成的模拟数据，
并通过 `source` 字段标注来源（akshare / mock），保证前端任何情况下都有数据可渲染。
"""
from __future__ import annotations

import random
import datetime as dt
from functools import wraps

from cachetools import TTLCache

import requests

try:
    import akshare as ak
    AK_OK = True
except Exception:  # akshare 未安装也能跑（全部走 mock）
    ak = None
    AK_OK = False

# ---- 简单 TTL 缓存（按函数+参数） ----
_cache = TTLCache(maxsize=256, ttl=30)


def cached(ttl: int):
    def deco(fn):
        local = TTLCache(maxsize=64, ttl=ttl)

        @wraps(fn)
        def wrapper(*args, **kwargs):
            key = (fn.__name__, args, tuple(sorted(kwargs.items())))
            if key in local:
                return local[key]
            val = fn(*args, **kwargs)
            local[key] = val
            return val

        return wrapper

    return deco


def _rnd(a, b):
    return round(random.uniform(a, b), 2)


# ============================================================
# 指数
# ============================================================
MAJOR_INDEX = {
    "sh000001": ("上证指数", 3210),
    "sz399001": ("深证成指", 10180),
    "sz399006": ("创业板指", 2105),
    "sh000300": ("沪深300", 3760),
    "bj899050": ("北证50", 1080),
}


@cached(10)
def get_indices():
    if AK_OK:
        try:
            df = ak.stock_zh_index_spot_sina()
            rows = []
            for code, (name, _base) in MAJOR_INDEX.items():
                r = df[df["代码"] == code]
                if r.empty:
                    continue
                r = r.iloc[0]
                rows.append({
                    "code": code, "name": name,
                    "price": float(r["最新价"]),
                    "change": float(r["涨跌额"]),
                    "pct": float(r["涨跌幅"]),
                })
            if rows:
                return {"source": "akshare", "list": rows}
        except Exception as e:  # noqa
            pass
    # mock
    rows = []
    for code, (name, base) in MAJOR_INDEX.items():
        pct = _rnd(-2.5, 2.5)
        price = round(base * (1 + pct / 100), 2)
        rows.append({"code": code, "name": name, "price": price,
                     "change": round(price - base, 2), "pct": pct})
    return {"source": "mock", "list": rows}


# ============================================================
# K线
# ============================================================
# ============================================================
# 实时报价（新浪 hq，速度快且稳定，用于盯盘预警）
# ============================================================
def realtime_quotes(codes):
    """返回 {code: {name, price, prev_close, pct, open, high, low}}。失败返回 {}。"""
    if not codes:
        return {}
    syms = ",".join(_sina_symbol(c) for c in codes)
    try:
        r = requests.get("https://hq.sinajs.cn/list=" + syms,
                         headers={"Referer": "https://finance.sina.com.cn"}, timeout=6)
        out = {}
        for line in r.text.split(";\n"):
            if "hq_str_" not in line or '="' not in line:
                continue
            head, body = line.split('="', 1)
            sym = head.split("hq_str_")[1].strip()
            code = sym[2:]
            f = body.strip('"').split(",")
            if len(f) < 6 or not f[3]:
                continue
            price = float(f[3]); prev = float(f[2]) if f[2] else 0.0
            out[code] = {"name": f[0], "open": float(f[1] or 0), "prev_close": prev,
                         "price": price, "high": float(f[4] or 0), "low": float(f[5] or 0),
                         "pct": round((price - prev) / prev * 100, 2) if prev else 0.0}
        return out
    except Exception:
        return {}


# ============================================================
# 资讯新闻
# ============================================================
_BULL = ["涨停", "利好", "增长", "大涨", "突破", "中标", "签约", "回购", "增持", "扭亏",
         "超预期", "新高", "提价", "涨价", "订单", "合作", "获批", "盈利", "分红", "重组",
         "并购", "补贴", "减税", "降准", "降息", "刺激", "国产替代", "放量", "净流入"]
_BEAR = ["跌停", "利空", "下滑", "大跌", "亏损", "减持", "处罚", "退市", "违规", "下调",
         "不及预期", "新低", "停牌", "质押", "爆雷", "诉讼", "解禁", "商誉", "预亏", "降价",
         "裁员", "债务", "暴跌", "净流出", "风险警示"]


def judge_sentiment(text: str):
    t = text or ""
    pos = [w for w in _BULL if w in t]
    neg = [w for w in _BEAR if w in t]
    if len(pos) > len(neg):
        return "利好", pos[:4]
    if len(neg) > len(pos):
        return "利空", neg[:4]
    return "中性", (pos or neg)[:4]


@cached(120)
def get_news(limit: int = 40):
    if AK_OK:
        try:
            df = ak.stock_info_global_em()
            rows = []
            for _, r in df.head(limit).iterrows():
                title = str(r["标题"]); summary = str(r.get("摘要", ""))
                senti, kw = judge_sentiment(title + summary)
                rows.append({"time": str(r["发布时间"]), "title": title, "summary": summary,
                             "url": str(r.get("链接", "")), "sentiment": senti, "keywords": kw})
            if rows:
                return {"source": "akshare", "list": rows}
        except Exception:
            pass
    return {"source": "mock", "list": [
        {"time": "—", "title": "示例资讯：市场情绪回暖，多板块走强", "summary": "（演示数据）",
         "sentiment": "利好", "keywords": ["利好"], "url": ""}]}


@cached(180)
def get_stock_news(code: str, limit: int = 12):
    if AK_OK:
        try:
            df = ak.stock_news_em(symbol=code)
            rows = []
            for _, r in df.head(limit).iterrows():
                title = str(r["新闻标题"]); content = str(r.get("新闻内容", ""))
                senti, kw = judge_sentiment(title + content)
                rows.append({"time": str(r["发布时间"]), "title": title,
                             "summary": content[:120], "source": str(r.get("文章来源", "")),
                             "url": str(r.get("新闻链接", "")), "sentiment": senti, "keywords": kw})
            if rows:
                return {"source": "akshare", "list": rows}
        except Exception:
            pass
    return {"source": "mock", "list": []}


def _sina_symbol(code: str) -> str:
    if code.startswith("6"):
        return "sh" + code
    if code.startswith(("0", "3")):
        return "sz" + code
    if code.startswith(("8", "4")):
        return "bj" + code
    return "sh" + code


@cached(60)
def get_kline(symbol: str = "600519", days: int = 120):
    if AK_OK:
        # 主源：新浪日线（更稳定）；备源：腾讯
        for src in ("sina", "tx"):
            try:
                sym = _sina_symbol(symbol)
                if src == "sina":
                    df = ak.stock_zh_a_daily(symbol=sym, adjust="qfq")
                else:
                    df = ak.stock_zh_a_hist_tx(symbol=sym)
                if df is not None and not df.empty:
                    df = df.tail(days)
                    dates = [str(d)[5:].replace("-", "/") for d in df["date"]]
                    ohlc = [[float(o), float(c), float(l), float(h)] for o, c, l, h in
                            zip(df["open"], df["close"], df["low"], df["high"])]
                    vols = [int(v) for v in (df["volume"] if "volume" in df.columns else df["amount"])]
                    return {"source": "akshare", "symbol": symbol, "dates": dates, "ohlc": ohlc, "vols": vols}
            except Exception:
                continue
    # mock
    dates, ohlc, vols = [], [], []
    price = 1680.0
    today = dt.date.today()
    for i in range(days, 0, -1):
        d = today - dt.timedelta(days=i)
        dates.append(f"{d.month}/{d.day}")
        o = price
        c = round(o + _rnd(-o * 0.03, o * 0.03), 2)
        h = round(max(o, c) + _rnd(0, o * 0.02), 2)
        l = round(min(o, c) - _rnd(0, o * 0.02), 2)
        ohlc.append([o, c, l, h])
        vols.append(int(_rnd(2, 9) * 1e6))
        price = c
    return {"source": "mock", "symbol": symbol, "dates": dates, "ohlc": ohlc, "vols": vols}


# ============================================================
# 行业板块（云图 / 热门板块复用）—— 新浪行业（东财push2在部分网络被封）
# ============================================================
@cached(60)
def get_industry_boards():
    if AK_OK:
        try:
            df = ak.stock_sector_spot(indicator="新浪行业")
            rows = []
            for _, r in df.iterrows():
                rows.append({
                    "name": str(r["板块"]),
                    "pct": float(r["涨跌幅"]),
                    "amount": round(float(r["总成交额"]) / 1e8, 1),  # 亿
                    "count": int(r.get("公司家数", 0) or 0),
                    "leader": str(r.get("股票名称", "")),
                })
            if rows:
                rows.sort(key=lambda x: x["pct"], reverse=True)
                return {"source": "akshare", "list": rows}
        except Exception:
            pass
    sectors = ["半导体", "新能源", "医药生物", "白酒食品", "军工", "证券", "银行",
               "房地产", "人工智能", "消费电子", "光伏", "汽车", "有色金属", "煤炭", "传媒"]
    return {"source": "mock", "list": [
        {"name": s, "pct": _rnd(-3, 6), "amount": _rnd(50, 500),
         "count": int(_rnd(10, 80)), "leader": "龙头股"} for s in sectors]}


# ============================================================
# 全市场快照（情绪 / 全市场云图）
# ============================================================
@cached(60)
def _spot():
    if AK_OK:
        try:
            df = ak.stock_zh_a_spot_em()
            if df is not None and not df.empty:
                return df
        except Exception:
            pass
    return None


@cached(30)
def get_sentiment():
    if AK_OK:
        try:
            df = ak.stock_market_activity_legu()
            m = {}
            for _, r in df.iterrows():
                m[str(r["item"]).strip()] = r["value"]

            def num(k):
                try:
                    return int(float(m.get(k, 0)))
                except Exception:
                    return 0
            up, down, flat = num("上涨"), num("下跌"), num("平盘")
            if up or down:
                return {"source": "akshare", "up": up, "down": down, "flat": flat,
                        "limit_up": num("涨停"), "limit_down": num("跌停"),
                        "height": min(9, max(3, num("涨停") // 8))}
        except Exception:
            pass
    up, down, flat = int(_rnd(1800, 3200)), int(_rnd(1200, 2600)), int(_rnd(80, 260))
    return {"source": "mock", "up": up, "down": down, "flat": flat,
            "limit_up": int(_rnd(20, 90)), "limit_down": int(_rnd(2, 30)), "height": int(_rnd(4, 9))}


@cached(60)
def get_treemap(mode: str = "sector"):
    if mode == "all":
        df = _spot()
        if df is not None:
            try:
                top = df.sort_values("成交额", ascending=False).head(150)
                items = [{"name": str(r["名称"]), "value": round(float(r["成交额"]) / 1e8, 2),
                          "pct": float(r["涨跌幅"])} for _, r in top.iterrows()]
                return {"source": "akshare", "mode": "all", "items": items}
            except Exception:
                pass
        # mock flat
        items = [{"name": f"个股{i}", "value": _rnd(2, 50), "pct": _rnd(-9, 9)} for i in range(60)]
        return {"source": "mock", "mode": "all", "items": items}
    # sector
    boards = get_industry_boards()
    items = [{"name": b["name"], "value": b.get("amount", 1), "pct": b["pct"]} for b in boards["list"]]
    return {"source": boards["source"], "mode": "sector", "items": items}


# ============================================================
# 资金流向（行业）
# ============================================================
@cached(60)
def get_fund_flow():
    if AK_OK:
        try:
            df = ak.stock_fund_flow_industry(symbol="即时")
            rows = []
            for _, r in df.iterrows():
                rows.append({"name": str(r["行业"]),
                             "net": round(float(r["净额"]), 2),  # 同花顺已是亿元
                             "pct": float(r["行业-涨跌幅"])})
            if rows:
                rows.sort(key=lambda x: x["net"])
                # 取首尾各15条，突出流入流出两端
                show = rows[:15] + rows[-15:] if len(rows) > 30 else rows
                show.sort(key=lambda x: x["net"])
                return {"source": "akshare", "list": show}
        except Exception:
            pass
    sectors = ["半导体", "新能源", "医药生物", "白酒食品", "军工", "证券", "银行",
               "房地产", "人工智能", "消费电子", "光伏", "汽车", "有色金属", "煤炭", "传媒"]
    rows = [{"name": s, "net": _rnd(-40, 60), "pct": _rnd(-3, 6)} for s in sectors]
    rows.sort(key=lambda x: x["net"])
    return {"source": "mock", "list": rows}


# ============================================================
# 热门股票（人气榜）
# ============================================================
@cached(60)
def get_hot_stocks():
    if AK_OK:
        try:
            df = ak.stock_hot_rank_em()
            rows = []
            for _, r in df.head(20).iterrows():
                rows.append({"rank": int(r["当前排名"]), "code": str(r["代码"]),
                             "name": str(r["股票名称"]), "price": float(r["最新价"]),
                             "pct": float(r["涨跌幅"])})
            if rows:
                return {"source": "akshare", "list": rows}
        except Exception:
            pass
    pool = ["龙头A", "龙头B", "中军C", "黑马D", "次新E", "蓝筹F", "题材G", "妖股H"]
    return {"source": "mock", "list": [
        {"rank": i + 1, "code": f"60{1000+i}", "name": f"{pool[i % len(pool)]}{i}",
         "price": _rnd(5, 200), "pct": _rnd(-5, 11)} for i in range(15)]}


# ============================================================
# 龙虎榜
# ============================================================
@cached(300)
def get_dragon_tiger():
    if AK_OK:
        try:
            for back in range(0, 7):
                d = (dt.date.today() - dt.timedelta(days=back)).strftime("%Y%m%d")
                try:
                    df = ak.stock_lhb_detail_em(start_date=d, end_date=d)
                except Exception:
                    df = None
                if df is not None and not df.empty:
                    rows = []
                    for _, r in df.head(20).iterrows():
                        rows.append({
                            "code": str(r.get("代码", "")), "name": str(r.get("名称", "")),
                            "pct": float(r.get("涨跌幅", 0) or 0),
                            "net": round(float(r.get("龙虎榜净买额", 0) or 0) / 1e8, 2),
                            "reason": str(r.get("上榜原因", "")),
                        })
                    return {"source": "akshare", "date": d, "list": rows}
        except Exception:
            pass
    pool = ["龙头A", "龙头B", "中军C", "黑马D"]
    return {"source": "mock", "date": "", "list": [
        {"code": f"60{1000+i}", "name": f"{pool[i % len(pool)]}{i}", "pct": _rnd(-3, 10),
         "net": _rnd(-3, 5), "reason": ["日涨幅偏离", "换手率达20%", "连续三日涨停"][i % 3]} for i in range(12)]}


# ============================================================
# 自选股 —— 代码名称表 + 个股日线（push2 被封时的稳妥方案）
# ============================================================
@cached(3600)
def _code_name_map():
    if AK_OK:
        try:
            cn = ak.stock_info_a_code_name()
            return {str(r["code"]): str(r["name"]) for _, r in cn.iterrows()}
        except Exception:
            pass
    return {}


def get_watchlist(symbols: list[str]):
    names = {"600519": "贵州茅台", "300750": "宁德时代", "002594": "比亚迪",
             "688981": "中芯国际", "300059": "东方财富", "601012": "隆基绿能"}
    if AK_OK:
        cmap = _code_name_map()
        rows = []
        for s in symbols:
            try:
                k = get_kline(s, 30)
                if k["source"] != "akshare" or len(k["ohlc"]) < 2:
                    continue
                last, prev = k["ohlc"][-1], k["ohlc"][-2]
                price, prev_close = last[1], prev[1]
                change = round(price - prev_close, 2)
                pct = round(change / prev_close * 100, 2) if prev_close else 0.0
                rows.append({"code": s, "name": cmap.get(s, names.get(s, s)), "price": price,
                             "pct": pct, "change": change,
                             "amount": round(k["vols"][-1] * price / 1e8, 2)})
            except Exception:
                continue
        if rows:
            return {"source": "akshare", "list": rows}
    return {"source": "mock", "list": [
        {"code": c, "name": names.get(c, c), "price": _rnd(20, 1800), "pct": _rnd(-4, 5),
         "change": _rnd(-30, 30), "amount": _rnd(3, 60)} for c in symbols]}