revert: 去掉我误建的macro_index_collector(莫荷的macro_context_collector已覆盖)
爹在XMPP里和我(知微)商量的宏观预警系统就是这3个文件: macro_context_collector.py — 宏观新闻采集+指数采集+红绿灯 divergence_detector.py — 跨市场背离 macro_signal_consumer.py — 风险信号消费 我不该另建macro_index_collector，现已删除，cron已恢复指向原文件
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知微
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#!/usr/bin/env python3
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"""macro_index_collector.py — 指数宏观数据采集 (no_agent)
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采集指数行情，写入 macro_context_log 表（积累每日快照）。
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与莫荷的 macro_context_collector.py（宏观新闻采集）分开，互不冲突。
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在 9:35 和 12:00 由 cron 触发。
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"""
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import json, sqlite3, subprocess
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from datetime import datetime
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from pathlib import Path
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DATA_DIR = Path("/home/hmo/web-dashboard/data")
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DB_PATH = Path("/home/hmo/MoFin/data/mofin.db")
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INDICES = [
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("sh000001", "上证指数"), ("sz399001", "深证成指"),
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("sz399006", "创业板指"), ("sh000688", "科创50"),
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("hkHSI", "恒生指数"), ("hkHSCEI", "国企指数"),
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]
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SECTOR_INDICES = [
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("sz980017", "国证芯片"), ("sh000039", "上证信息"),
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("sz980022", "机器人产业"), ("sz980032", "新能电池"),
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("sz980076", "通用航空"), ("sh000063", "上证周期"),
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("sh000068", "上证资源"), ("sh000019", "治理指数"),
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]
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def fetch(symbol):
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try:
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r = subprocess.run(["curl", "-s", f"https://qt.gtimg.cn/q={symbol}"],
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capture_output=True, timeout=8)
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return r.stdout.decode("gbk", errors="replace")
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except:
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return None
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def parse(text, name):
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if not text or "pv_none_match" in text:
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return None
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try:
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f = text.split("~")
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if len(f) < 35:
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return None
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price = float(f[3]) if f[3] else 0
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prev = float(f[4]) if f[4] else 0
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high = float(f[33]) if len(f) > 33 and f[33] else 0
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low = float(f[34]) if len(f) > 34 and f[34] else 0
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chg = round((price - prev) / prev * 100, 2) if prev else 0
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return {"name": name, "price": price, "change_pct": chg,
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"high": high, "low": low}
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except:
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return None
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def assess(indices_data):
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if not indices_data:
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return "unknown", "unknown"
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sh = next((i for i in indices_data if i and i["name"] == "上证指数"), None)
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sz = next((i for i in indices_data if i and i["name"] == "深证成指"), None)
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cyb = next((i for i in indices_data if i and i["name"] == "创业板指"), None)
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avg = ((sh or {}).get("change_pct", 0) + (sz or {}).get("change_pct", 0) +
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(cyb or {}).get("change_pct", 0)) / 3
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if avg > 1.5:
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return "strong_bullish", "整体强势"
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elif avg > 0.5:
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return "bullish", "偏强"
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elif avg > -0.5:
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return "neutral", "震荡"
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elif avg > -1.5:
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return "bearish", "偏弱"
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return "strong_bearish", "整体弱势"
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def main():
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now = datetime.now()
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indices_data = []
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for sym, name in INDICES:
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raw = fetch(sym)
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p = parse(raw, name)
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if p:
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indices_data.append(p)
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has_data = any(i for i in indices_data if i and i.get("price", 0) > 0)
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overall, desc = assess(indices_data)
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# 读莫荷的 macro_risk_state.json 补充风险状态
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risk_state = {}
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try:
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risk_path = DATA_DIR / "macro_risk_state.json"
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if risk_path.exists():
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risk_state = json.loads(risk_path.read_text())
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except:
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pass
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context = {
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"updated_at": now.strftime("%Y-%m-%d %H:%M:%S"),
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"session": "morning" if now.hour < 12 else "midday",
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"has_valid_data": has_data,
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"indices": {i["name"]: {"price": i["price"], "change_pct": i["change_pct"],
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"high": i.get("high", 0), "low": i.get("low", 0)}
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for i in indices_data if i},
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"structure": {"overall": overall, "description": desc},
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"risk_level": risk_state.get("level", "none"),
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"risk_reason": risk_state.get("reason", ""),
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}
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# 写入DB
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try:
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conn = sqlite3.connect(str(DB_PATH))
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conn.execute('''INSERT INTO macro_context_log
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(data_timestamp, session, has_valid_data, indices, structure,
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key_sectors, top_gainers, top_losers, sector_up_ratio, sector_mood)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)''',
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(context["updated_at"], context["session"],
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1 if has_data else 0,
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json.dumps(context["indices"], ensure_ascii=False),
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json.dumps(context["structure"], ensure_ascii=False),
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"[]", "[]", "[]", 0, overall))
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conn.commit()
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conn.close()
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except:
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pass
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# 写入 macro_context.json（兼容旧读取方）
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try:
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DATA_DIR.mkdir(parents=True, exist_ok=True)
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(DATA_DIR / "macro_context.json").write_text(
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json.dumps(context, ensure_ascii=False, indent=2))
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except:
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pass
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if has_data:
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idx_parts = [f"{i['name']}{'▲' if i['change_pct']>0 else '▼'}{i['change_pct']:+.2f}%"
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for i in indices_data[:4] if i]
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print(f"【宏观指数】{now.strftime('%H:%M')} | {desc}")
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print(" | ".join(idx_parts))
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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'}")
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if risk_state.get("level") == "high":
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print(f"🔴 宏观风险: {risk_state.get('reason','')}")
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else:
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print("【宏观指数】数据不可用（非交易时段或行情未更新）")
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if __name__ == "__main__":
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main()
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