#!/usr/bin/env python3
"""macro_index_collector.py — 指数宏观数据采集 (no_agent)

采集指数行情，写入 macro_context_log 表（积累每日快照）。
与莫荷的 macro_context_collector.py（宏观新闻采集）分开，互不冲突。

在 9:35 和 12:00 由 cron 触发。
"""

import json, sqlite3, subprocess
from datetime import datetime
from pathlib import Path

DATA_DIR = Path("/home/hmo/web-dashboard/data")
DB_PATH = Path("/home/hmo/MoFin/data/mofin.db")

INDICES = [
    ("sh000001", "上证指数"), ("sz399001", "深证成指"),
    ("sz399006", "创业板指"), ("sh000688", "科创50"),
    ("hkHSI", "恒生指数"), ("hkHSCEI", "国企指数"),
]

SECTOR_INDICES = [
    ("sz980017", "国证芯片"), ("sh000039", "上证信息"),
    ("sz980022", "机器人产业"), ("sz980032", "新能电池"),
    ("sz980076", "通用航空"), ("sh000063", "上证周期"),
    ("sh000068", "上证资源"), ("sh000019", "治理指数"),
]


def fetch(symbol):
    try:
        r = subprocess.run(["curl", "-s", f"https://qt.gtimg.cn/q={symbol}"],
                          capture_output=True, timeout=8)
        return r.stdout.decode("gbk", errors="replace")
    except:
        return None


def parse(text, name):
    if not text or "pv_none_match" in text:
        return None
    try:
        f = text.split("~")
        if len(f) < 35:
            return None
        price = float(f[3]) if f[3] else 0
        prev = float(f[4]) if f[4] else 0
        high = float(f[33]) if len(f) > 33 and f[33] else 0
        low = float(f[34]) if len(f) > 34 and f[34] else 0
        chg = round((price - prev) / prev * 100, 2) if prev else 0
        return {"name": name, "price": price, "change_pct": chg,
                "high": high, "low": low}
    except:
        return None


def assess(indices_data):
    if not indices_data:
        return "unknown", "unknown"
    sh = next((i for i in indices_data if i and i["name"] == "上证指数"), None)
    sz = next((i for i in indices_data if i and i["name"] == "深证成指"), None)
    cyb = next((i for i in indices_data if i and i["name"] == "创业板指"), None)
    avg = ((sh or {}).get("change_pct", 0) + (sz or {}).get("change_pct", 0) +
           (cyb or {}).get("change_pct", 0)) / 3
    if avg > 1.5:
        return "strong_bullish", "整体强势"
    elif avg > 0.5:
        return "bullish", "偏强"
    elif avg > -0.5:
        return "neutral", "震荡"
    elif avg > -1.5:
        return "bearish", "偏弱"
    return "strong_bearish", "整体弱势"


def main():
    now = datetime.now()
    indices_data = []
    for sym, name in INDICES:
        raw = fetch(sym)
        p = parse(raw, name)
        if p:
            indices_data.append(p)

    has_data = any(i for i in indices_data if i and i.get("price", 0) > 0)
    overall, desc = assess(indices_data)

    # 读莫荷的 macro_risk_state.json 补充风险状态
    risk_state = {}
    try:
        risk_path = DATA_DIR / "macro_risk_state.json"
        if risk_path.exists():
            risk_state = json.loads(risk_path.read_text())
    except:
        pass

    context = {
        "updated_at": now.strftime("%Y-%m-%d %H:%M:%S"),
        "session": "morning" if now.hour < 12 else "midday",
        "has_valid_data": has_data,
        "indices": {i["name"]: {"price": i["price"], "change_pct": i["change_pct"],
                                "high": i.get("high", 0), "low": i.get("low", 0)}
                    for i in indices_data if i},
        "structure": {"overall": overall, "description": desc},
        "risk_level": risk_state.get("level", "none"),
        "risk_reason": risk_state.get("reason", ""),
    }

    # 写入DB
    try:
        conn = sqlite3.connect(str(DB_PATH))
        conn.execute('''INSERT INTO macro_context_log
            (data_timestamp, session, has_valid_data, indices, structure,
             key_sectors, top_gainers, top_losers, sector_up_ratio, sector_mood)
            VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
            (context["updated_at"], context["session"],
             1 if has_data else 0,
             json.dumps(context["indices"], ensure_ascii=False),
             json.dumps(context["structure"], ensure_ascii=False),
             "[]", "[]", "[]", 0, overall))
        conn.commit()
        conn.close()
    except:
        pass

    # 写入 macro_context.json（兼容旧读取方）
    try:
        DATA_DIR.mkdir(parents=True, exist_ok=True)
        (DATA_DIR / "macro_context.json").write_text(
            json.dumps(context, ensure_ascii=False, indent=2))
    except:
        pass

    if has_data:
        idx_parts = [f"{i['name']}{'▲' if i['change_pct']>0 else '▼'}{i['change_pct']:+.2f}%"
                     for i in indices_data[:4] if i]
        print(f"【宏观指数】{now.strftime('%H:%M')} | {desc}")
        print(" | ".join(idx_parts))
        print(f"评估: {'整体强势' if overall=='strong_bullish' else '偏强' if overall=='bullish' else '震荡' if overall=='neutral' else '偏弱' if overall=='bearish' else '整体弱势'}")
        if risk_state.get("level") == "high":
            print(f"🔴 宏观风险: {risk_state.get('reason','')}")
    else:
        print("【宏观指数】数据不可用（非交易时段或行情未更新）")


if __name__ == "__main__":
    main()