#!/usr/bin/env python3
"""
macro_signal_consumer.py — 消费宏观风险信号，写入风险状态

no_agent 模式：有HIGH风险→输出风险摘要 | 无→静默

管道位置：
  macro_risk_scanner (8:30/11:30) → signal_news(source=macro_watch) → 本脚本
  ↓
  macro_risk_state.json — 供所有监控 cron 读取
  ↓
  如果 HIGH → 推送到 Dad
"""
import sqlite3, json, os, sys, time
from pathlib import Path
from datetime import datetime

BASE = Path("/home/hmo/MoFin")
DATA = BASE / "data"
DB_PATH = DATA / "mofin.db"
STATE_PATH = DATA / "macro_risk_state.json"

def db_update(conn, sql, params, max_retries=3):
    """幂等DB更新，遇到锁自动重试"""
    for attempt in range(max_retries):
        try:
            conn.execute(sql, params)
            conn.commit()
            return True
        except sqlite3.OperationalError as e:
            if "locked" in str(e).lower():
                if attempt < max_retries - 1:
                    time.sleep(1)
                continue
            raise
    print(f"[MACRO-CONSUMER] DB更新失败（持续锁）: {sql}", file=sys.stderr)
    return False

def main():
    conn = sqlite3.connect(str(DB_PATH), timeout=10)
    conn.execute("PRAGMA busy_timeout=5000")
    conn.row_factory = sqlite3.Row

    # 读取未处理的 macro_watch 信号
    rows = conn.execute(
        "SELECT * FROM signal_news WHERE source='macro_watch' AND (processed=0 OR processed IS NULL)"
    ).fetchall()

    if not rows:
        # 无新信号时状态文件维持 15 分钟过期
        try:
            state = json.loads(STATE_PATH.read_text())
            created = datetime.strptime(state.get("created_at", "2000-01-01"), "%Y-%m-%d %H:%M:%S")
            if (datetime.now() - created).total_seconds() > 900:  # 15 min
                state["level"] = "none"
                state["expired"] = True
                STATE_PATH.write_text(json.dumps(state, ensure_ascii=False, indent=2))
        except:
            pass
        conn.close()
        return  # SILENT

    # 聚合风险等级（考虑修正覆盖信号）
    levels = {"宏观-WATCH_HIGH": "high", "宏观-WATCH_MEDIUM": "medium", "宏观-WATCH_INFO": "info"}
    highest = "info"
    all_summaries = []
    
    def _effective_level(sentiment, summary):
        """修正覆盖信号取修正后的级别，不按原始sentiment算"""
        if "修正覆盖" in (summary or ""):
            s = (summary or "").lower()
            # 明确说零风险/正面/利好 → info
            if any(kw in s for kw in ["零风险", "正面利好", "正面进展", "非风险", "利好"]):
                return "info"
            # 明确说MEDIUM → medium
            if "medium" in s or "中风险" in s:
                return "medium"
            # 修正覆盖HIGH → 默认降为medium（不保留原始HIGH）
            return "medium"
        return levels.get(sentiment, "info")
    
    for r in rows:
        sentiment = r["overall_sentiment"]
        lv = _effective_level(sentiment, r["summary"])
        if lv == "high":
            highest = "high"
        elif lv == "medium" and highest != "high":
            highest = "medium"
        all_summaries.append({
            "sentiment": sentiment,
            "summary": r["summary"][:300],
            "key_articles": r["key_articles"],
            "created_at": r["created_at"],
        })

    # 写入风险状态文件
    state = {
        "level": highest,
        "signals": all_summaries,
        "signal_count": len(rows),
        "created_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
        "expired": False,
    }
    STATE_PATH.write_text(json.dumps(state, ensure_ascii=False, indent=2))

    # 标记为已处理（含重试）
    for r in rows:
        db_update(conn, "UPDATE signal_news SET processed=1 WHERE id=?", (r["id"],))
    conn.close()

    # no_agent 输出（有 HIGH 才主动出声）
    if highest == "high":
        print(f"[MACRO-RISK] ⚠️ HIGH: {len(rows)}条高风险信号")
        for s in all_summaries:
            print(f"  {s['summary'][:100]}")
    elif highest == "medium":
        if len(os.environ.get("MACRO_VERBOSE", "")) > 0:
            print(f"[MACRO-RISK] MEDIUM: {len(rows)}条中风险信号")
    # HIGH 信号会通过 no_agent 推送到 XMPP

if __name__ == "__main__":
    main()