知微
123 lines
4.3 KiB
Python
123 lines
4.3 KiB
Python
#!/usr/bin/env python3
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"""
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macro_signal_consumer.py — 消费宏观风险信号，写入风险状态
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no_agent 模式：有HIGH风险→输出风险摘要 | 无→静默
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管道位置：
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macro_risk_scanner (8:30/11:30) → signal_news(source=macro_watch) → 本脚本
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↓
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macro_risk_state.json — 供所有监控 cron 读取
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↓
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如果 HIGH → 推送到 Dad
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"""
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import sqlite3, json, os, sys, time
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from pathlib import Path
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from datetime import datetime
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BASE = Path("/home/hmo/MoFin")
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DATA = BASE / "data"
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DB_PATH = DATA / "mofin.db"
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STATE_PATH = DATA / "macro_risk_state.json"
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def db_update(conn, sql, params, max_retries=3):
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"""幂等DB更新，遇到锁自动重试"""
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for attempt in range(max_retries):
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try:
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conn.execute(sql, params)
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conn.commit()
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return True
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except sqlite3.OperationalError as e:
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if "locked" in str(e).lower():
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if attempt < max_retries - 1:
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time.sleep(1)
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continue
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raise
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print(f"[MACRO-CONSUMER] DB更新失败（持续锁）: {sql}", file=sys.stderr)
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return False
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def main():
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conn = sqlite3.connect(str(DB_PATH), timeout=10)
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conn.execute("PRAGMA busy_timeout=5000")
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conn.row_factory = sqlite3.Row
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# 读取未处理的 macro_watch 信号
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rows = conn.execute(
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"SELECT * FROM signal_news WHERE source='macro_watch' AND (processed=0 OR processed IS NULL)"
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).fetchall()
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if not rows:
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# 无新信号时状态文件维持 15 分钟过期
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try:
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state = json.loads(STATE_PATH.read_text())
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created = datetime.strptime(state.get("created_at", "2000-01-01"), "%Y-%m-%d %H:%M:%S")
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if (datetime.now() - created).total_seconds() > 900: # 15 min
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state["level"] = "none"
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state["expired"] = True
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STATE_PATH.write_text(json.dumps(state, ensure_ascii=False, indent=2))
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except:
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pass
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conn.close()
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return # SILENT
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# 聚合风险等级（考虑修正覆盖信号）
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levels = {"宏观-WATCH_HIGH": "high", "宏观-WATCH_MEDIUM": "medium", "宏观-WATCH_INFO": "info"}
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highest = "info"
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all_summaries = []
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def _effective_level(sentiment, summary):
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"""修正覆盖信号取修正后的级别，不按原始sentiment算"""
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if "修正覆盖" in (summary or ""):
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s = (summary or "").lower()
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# 明确说零风险/正面/利好 → info
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if any(kw in s for kw in ["零风险", "正面利好", "正面进展", "非风险", "利好"]):
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return "info"
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# 明确说MEDIUM → medium
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if "medium" in s or "中风险" in s:
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return "medium"
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# 修正覆盖HIGH → 默认降为medium（不保留原始HIGH）
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return "medium"
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return levels.get(sentiment, "info")
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for r in rows:
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sentiment = r["overall_sentiment"]
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lv = _effective_level(sentiment, r["summary"])
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if lv == "high":
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highest = "high"
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elif lv == "medium" and highest != "high":
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highest = "medium"
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all_summaries.append({
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"sentiment": sentiment,
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"summary": r["summary"][:300],
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"key_articles": r["key_articles"],
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"created_at": r["created_at"],
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})
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# 写入风险状态文件
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state = {
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"level": highest,
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"signals": all_summaries,
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"signal_count": len(rows),
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"created_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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"expired": False,
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}
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STATE_PATH.write_text(json.dumps(state, ensure_ascii=False, indent=2))
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# 标记为已处理（含重试）
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for r in rows:
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db_update(conn, "UPDATE signal_news SET processed=1 WHERE id=?", (r["id"],))
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conn.close()
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# no_agent 输出（有 HIGH 才主动出声）
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if highest == "high":
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print(f"[MACRO-RISK] ⚠️ HIGH: {len(rows)}条高风险信号")
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for s in all_summaries:
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print(f" {s['summary'][:100]}")
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elif highest == "medium":
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if len(os.environ.get("MACRO_VERBOSE", "")) > 0:
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print(f"[MACRO-RISK] MEDIUM: {len(rows)}条中风险信号")
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# HIGH 信号会通过 no_agent 推送到 XMPP
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if __name__ == "__main__":
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main()
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