trend_detector + xiaoguo_news_processor 全链路

- trend_detector.py: 6类信号检测（资金异动/涨跌比反转/领涨更替/趋势拐点/量价背离/普涨背离）
- xiaoguo_news_processor.py: akshare搜新闻+小果LLM情感分析
- mofin_db.py: 新增 sector_signals + signal_news 两张表
- 文档更新：新增第四章实时信号检测与小果情报处理
- 测试结果：趋势检测已通过，信号写入正常

mofin_db.py

@@ -291,6 +291,36 @@ def init_all_tables(conn: sqlite3.Connection):
             created_at      TEXT DEFAULT (datetime('now','localtime'))
         );
         CREATE INDEX IF NOT EXISTS idx_feedback_code ON strategy_feedback(code);
+
+        -- 板块信号（trend_detector 产出）
+        CREATE TABLE IF NOT EXISTS sector_signals (
+            id              INTEGER PRIMARY KEY AUTOINCREMENT,
+            signal_type     TEXT NOT NULL,
+            sector          TEXT NOT NULL,
+            severity        TEXT DEFAULT 'medium',
+            related_stocks  TEXT,
+            holdings_in_sector TEXT,
+            watchlist_in_sector TEXT,
+            trigger_reason  TEXT,
+            snapshot_id     INTEGER,
+            processed       INTEGER DEFAULT 0,
+            detected_at     TEXT DEFAULT (datetime('now','localtime'))
+        );
+        CREATE INDEX IF NOT EXISTS idx_signal_processed ON sector_signals(processed);
+        CREATE INDEX IF NOT EXISTS idx_signal_sector ON sector_signals(sector);
+
+        -- 小果情报（xiaoguo_news_processor 产出）
+        CREATE TABLE IF NOT EXISTS signal_news (
+            id              INTEGER PRIMARY KEY AUTOINCREMENT,
+            signal_id       INTEGER REFERENCES sector_signals(id),
+            sector          TEXT NOT NULL,
+            overall_sentiment TEXT,
+            summary         TEXT,
+            key_articles    TEXT,
+            searched_stocks TEXT,
+            created_at      TEXT DEFAULT (datetime('now','localtime'))
+        );
+        CREATE INDEX IF NOT EXISTS idx_signal_news_signal ON signal_news(signal_id);
     """)
     conn.commit()
 

trend_detector.py

@@ -0,0 +1,303 @@
+#!/usr/bin/env python3
+"""trend_detector.py — 板块异常信号检测
+
+配合 market_watch（每30分）运行，从最新 snapshot 中检测6类信号：
+  1. 资金异动 — 净流入/出远超近期均值
+  2. 涨跌比反转 — 板块内涨跌家数比例突变
+  3. 领涨股更替 — 领涨股换人
+  4. 趋势拐点 — 连续流入→转流出 或 连续流出→转入流
+  5. 量价背离 — 涨但资金流出 / 跌但资金流入
+  6. 普涨背离 — 板块大涨但上涨家数<50%
+
+检测到信号后写入 sector_signals 表。
+"""
+
+import json
+import sqlite3
+import sys
+from datetime import datetime
+from pathlib import Path
+
+DATA_DIR = Path(__file__).parent / "data"
+DB_PATH = DATA_DIR / "mofin.db"
+
+
+def get_conn():
+    conn = sqlite3.connect(str(DB_PATH))
+    conn.row_factory = sqlite3.Row
+    return conn
+
+
+def get_recent_snapshots(conn, n=20):
+    """取最近 n 次 market_snapshots"""
+    return conn.execute(
+        "SELECT id, timestamp, up_ratio, mood FROM market_snapshots ORDER BY id DESC LIMIT ?",
+        (n,)
+    ).fetchall()
+
+
+def get_sectors_for_snapshot(conn, snapshot_id):
+    """取指定 snapshot 的全部板块数据"""
+    rows = conn.execute(
+        "SELECT * FROM sector_snapshots WHERE snapshot_id = ?", (snapshot_id,)
+    ).fetchall()
+    return [dict(r) for r in rows]
+
+
+def get_sector_history(conn, sector_name, n=20):
+    """取某板块最近 n 次采集记录"""
+    return conn.execute("""
+        SELECT ss.*, ms.timestamp
+        FROM sector_snapshots ss
+        JOIN market_snapshots ms ON ss.snapshot_id = ms.id
+        WHERE ss.name = ?
+        ORDER BY ms.id DESC LIMIT ?
+    """, (sector_name, n)).fetchall()
+
+
+def get_holdings(conn):
+    """取活跃持仓"""
+    return conn.execute("SELECT code, name FROM holdings WHERE is_active=1").fetchall()
+
+
+def get_watchlist(conn):
+    """取活跃自选"""
+    return conn.execute("SELECT code, name FROM watchlist_stocks WHERE is_active=1").fetchall()
+
+
+def get_sector_for_stock(conn, code):
+    """查个股对应的板块"""
+    row = conn.execute(
+        "SELECT sector_name FROM stock_sectors WHERE code = ?", (code,)
+    ).fetchone()
+    return row[0] if row else None
+
+
+def write_signal(conn, signal_type, sector, severity, related_stocks,
+                 holdings_list, watchlist_list, trigger_reason, snapshot_id):
+    """写入信号到 sector_signals"""
+    # 同板块同类型24小时内已有信号则跳过
+    existing = conn.execute("""
+        SELECT id FROM sector_signals
+        WHERE sector = ? AND signal_type = ?
+        AND datetime(detected_at) >= datetime('now', '-1 day')
+        LIMIT 1
+    """, (sector, signal_type)).fetchone()
+    if existing:
+        return False
+
+    conn.execute("""
+        INSERT INTO sector_signals
+        (signal_type, sector, severity, related_stocks,
+         holdings_in_sector, watchlist_in_sector,
+         trigger_reason, snapshot_id)
+        VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+    """, (
+        signal_type, sector, severity,
+        json.dumps(related_stocks, ensure_ascii=False),
+        json.dumps(holdings_list, ensure_ascii=False) if holdings_list else None,
+        json.dumps(watchlist_list, ensure_ascii=False) if watchlist_list else None,
+        trigger_reason, snapshot_id
+    ))
+    conn.commit()
+    return True
+
+
+def check_signals(conn, latest, prev_snapshots):
+    """对最新 snapshot 检测6类信号"""
+    latest_id = latest["id"]
+    sectors = get_sectors_for_snapshot(conn, latest_id)
+    if not sectors:
+        return
+
+    # 取持仓和自选
+    holdings = {r["code"]: r["name"] for r in get_holdings(conn)}
+    watchlist = {r["code"]: r["name"] for r in get_watchlist(conn)}
+
+    # 取上一次 snapshot 用于对比（如果有）
+    prev_id = None
+    if len(prev_snapshots) >= 2:
+        prev_id = prev_snapshots[1]["id"]
+    prev_sectors = get_sectors_for_snapshot(conn, prev_id) if prev_id else []
+
+    # 构建 name→sector 映射
+    prev_map = {s["name"]: s for s in prev_sectors}
+
+    for s in sectors:
+        name = s["name"]
+        change = s["change_pct"] or 0
+        net_inflow = s["net_inflow"] or 0
+        up_count = s["up_count"] or 0
+        down_count = s["down_count"] or 0
+        total = up_count + down_count
+        up_ratio = up_count / total if total > 0 else None
+        lead_stock = s["lead_stock"] or ""
+
+        # 近期历史
+        history = get_sector_history(conn, name, 20)
+
+        # 计算近期均值（后续多重信号共用）
+        mean = 0
+        if len(history) >= 3:
+            recent_inflows = [abs(h["net_inflow"] or 0) for h in history[:10]]
+            mean = sum(recent_inflows) / len(recent_inflows) if recent_inflows else 0
+
+        # 信号1：资金异动
+        if net_inflow and len(history) >= 5 and mean > 0:
+            recent_inflows = [abs(h["net_inflow"] or 0) for h in history[:20]]
+            new_mean = sum(recent_inflows) / len(recent_inflows)
+            std = (sum((x - new_mean) ** 2 for x in recent_inflows) / len(recent_inflows)) ** 0.5
+            if std > 0 and abs(net_inflow) > mean + 3 * std:
+                direction = "净流入" if net_inflow > 0 else "净流出"
+                sev = "high" if abs(net_inflow) > mean + 5 * std else "medium"
+                related = _get_related_stocks(conn, name, lead_stock, change)
+                holdings_list = _match_holdings(related, holdings)
+                watchlist_list = _match_holdings(related, watchlist)
+                ok = write_signal(conn, "资金异动", name, sev, related,
+                                  holdings_list, watchlist_list,
+                                  f"{direction}{abs(net_inflow):.0f}亿（均值{mean:.0f}亿，超{abs(net_inflow)/max(mean,0.01):.0f}倍）",
+                                  latest_id)
+                if ok:
+                    print(f"  ⚠️  资金异动 [{sev}] {name}: {direction}{abs(net_inflow):.0f}亿", flush=True)
+
+        # 信号2：涨跌比反转（相比上一次）
+        prev = dict(prev_map[name]) if name in prev_map else {}
+        if prev and up_ratio is not None and prev["up_count"] and prev["down_count"]:
+            prev_total = prev["up_count"] + prev["down_count"]
+            prev_ratio = prev["up_count"] / prev_total if prev_total > 0 else 0
+            if abs(up_ratio - prev_ratio) > 0.3:  # 涨跌比变化超过30个百分点
+                direction = "转强" if up_ratio > prev_ratio else "转弱"
+                sev = "high" if abs(up_ratio - prev_ratio) > 0.5 else "medium"
+                related = _get_related_stocks(conn, name, lead_stock, change)
+                holdings_list = _match_holdings(related, holdings)
+                watchlist_list = _match_holdings(related, watchlist)
+                ok = write_signal(conn, "涨跌比反转", name, sev, related,
+                                  holdings_list, watchlist_list,
+                                  f"上涨占比{prev_ratio*100:.0f}%→{up_ratio*100:.0f}%，{direction}",
+                                  latest_id)
+                if ok:
+                    print(f"  ⚠️  涨跌比反转 [{sev}] {name}: {prev_ratio*100:.0f}%→{up_ratio*100:.0f}% {direction}", flush=True)
+
+        # 信号3：领涨股更替
+        prev_lead = prev.get("lead_stock", "") if prev else ""
+        if lead_stock and prev_lead and lead_stock != prev_lead:
+            related = _get_related_stocks(conn, name, lead_stock, change)
+            holdings_list = _match_holdings(related, holdings)
+            watchlist_list = _match_holdings(related, watchlist)
+            ok = write_signal(conn, "领涨股更替", name, "medium", related,
+                              holdings_list, watchlist_list,
+                              f"领涨股从「{prev_lead}」换成「{lead_stock}」",
+                              latest_id)
+            if ok:
+                print(f"  ⚠️  领涨股更替 [{name}] {prev_lead} → {lead_stock}", flush=True)
+
+        # 信号4：趋势拐点（连续净流入突然转流出，反之亦然）
+        if net_inflow and len(history) >= 4:
+            recent = [h["net_inflow"] or 0 for h in history[:4]]
+            all_positive = all(r > 0 for r in recent[:3])
+            all_negative = all(r < 0 for r in recent[:3])
+            if all_positive and net_inflow < 0 and abs(net_inflow) > mean * 0.5:
+                related = _get_related_stocks(conn, name, lead_stock, change)
+                holdings_list = _match_holdings(related, holdings)
+                watchlist_list = _match_holdings(related, watchlist)
+                ok = write_signal(conn, "趋势拐点", name, "high", related,
+                                  holdings_list, watchlist_list,
+                                  f"连续3次净流入后转流出{abs(net_inflow):.0f}亿",
+                                  latest_id)
+                if ok:
+                    print(f"  ⚠️  趋势拐点 [high] {name}: 连续流入→转流出{abs(net_inflow):.0f}亿", flush=True)
+            elif all_negative and net_inflow > 0 and net_inflow > abs(sum(recent[:3])) * 0.5:
+                related = _get_related_stocks(conn, name, lead_stock, change)
+                holdings_list = _match_holdings(related, holdings)
+                watchlist_list = _match_holdings(related, watchlist)
+                ok = write_signal(conn, "趋势拐点", name, "high", related,
+                                  holdings_list, watchlist_list,
+                                  f"连续3次净流出后转入流{net_inflow:.0f}亿",
+                                  latest_id)
+                if ok:
+                    print(f"  ⚠️  趋势拐点 [high] {name}: 连续流出→转入流{net_inflow:.0f}亿", flush=True)
+
+        # 信号5：量价背离
+        if net_inflow and change and abs(change) > 2:
+            if change > 0 and net_inflow < -abs(mean or 1):
+                related = _get_related_stocks(conn, name, lead_stock, change)
+                holdings_list = _match_holdings(related, holdings)
+                watchlist_list = _match_holdings(related, watchlist)
+                ok = write_signal(conn, "量价背离", name, "medium", related,
+                                  holdings_list, watchlist_list,
+                                  f"板块涨{change:+.2f}%但资金净流出{abs(net_inflow):.0f}亿",
+                                  latest_id)
+                if ok:
+                    print(f"  ⚠️  量价背离 [{name}] 涨{change:+.2f}%但流出{abs(net_inflow):.0f}亿", flush=True)
+            elif change < 0 and net_inflow > abs(mean or 1):
+                related = _get_related_stocks(conn, name, lead_stock, change)
+                holdings_list = _match_holdings(related, holdings)
+                watchlist_list = _match_holdings(related, watchlist)
+                ok = write_signal(conn, "量价背离", name, "medium", related,
+                                  holdings_list, watchlist_list,
+                                  f"板块跌{change:+.2f}%但资金净流入{net_inflow:.0f}亿（吸筹信号）",
+                                  latest_id)
+                if ok:
+                    print(f"  ⚠️  量价背离 [{name}] 跌{change:+.2f}%但流入{net_inflow:.0f}亿（吸筹）", flush=True)
+
+        # 信号6：普涨背离
+        if up_ratio is not None and change > 3 and up_ratio < 0.5:
+            related = _get_related_stocks(conn, name, lead_stock, change)
+            holdings_list = _match_holdings(related, holdings)
+            watchlist_list = _match_holdings(related, watchlist)
+            ok = write_signal(conn, "普涨背离", name, "medium", related,
+                              holdings_list, watchlist_list,
+                              f"板块涨{change:+.2f}%但仅{up_count}/{total}家上涨（分化严重）",
+                              latest_id)
+            if ok:
+                print(f"  ⚠️  普涨背离 [{name}] 涨{change:+.2f}%但仅{up_count}/{total}家上涨", flush=True)
+
+
+def _get_related_stocks(conn, sector_name, lead_stock, change_pct):
+    """获取板块相关个股（领涨股 + board 成分股）"""
+    stocks = []
+    if lead_stock:
+        stocks.append({"name": lead_stock, "code": "", "change_pct": 0, "role": "领涨"})
+    # 从 stock_sectors 表取成分股
+    members = conn.execute(
+        "SELECT s.code, s.name FROM stocks s "
+        "JOIN stock_sectors ss ON s.code = ss.code "
+        "WHERE ss.sector_name = ? LIMIT 5",
+        (sector_name,)
+    ).fetchall()
+    for m in members:
+        if not any(s.get("name") == m["name"] for s in stocks):
+            stocks.append({"name": m["name"], "code": m["code"], "change_pct": 0, "role": "成分"})
+    return stocks
+
+
+def _match_holdings(stocks, holding_dict):
+    """匹配相关个股中的持仓/自选"""
+    matched = []
+    for s in stocks:
+        code = s.get("code", "")
+        if code in holding_dict:
+            matched.append({"code": code, "name": holding_dict[code]})
+    return matched
+
+
+def main():
+    conn = get_conn()
+
+    # 取最近 snapshots
+    snapshots = get_recent_snapshots(conn, 5)
+    if len(snapshots) < 2:
+        print(f"数据不足: 只有 {len(snapshots)} 次采集，需要至少2次", flush=True)
+        conn.close()
+        return
+
+    latest = dict(snapshots[0])
+    print(f"检测最新 snapshot: {latest['timestamp']} (id={latest['id']})", flush=True)
+
+    check_signals(conn, latest, snapshots)
+    conn.close()
+    print("检测完成", flush=True)
+
+
+if __name__ == "__main__":
+    main()

xiaoguo_news_processor.py

@@ -0,0 +1,202 @@
+#!/usr/bin/env python3
+"""xiaoguo_news_processor.py — 小果新闻情报处理
+
+配合 trend_detector（每30分）运行，处理未处理的 sector_signals。
+
+流程：
+  1. 读未 processed 的 signals（每次1条）
+  2. akshare 搜新闻（板块相关个股 + 持仓 + 自选）
+  3. 调小果 LLM 逐篇分析情感
+  4. 写入 signal_news
+  5. 标记 signal.processed = true
+"""
+
+import json
+import os
+import urllib.request
+from datetime import datetime
+from pathlib import Path
+
+try:
+    import akshare as ak
+    HAS_AKSHARE = True
+except ImportError:
+    HAS_AKSHARE = False
+
+DATA_DIR = Path(__file__).parent / "data"
+DB_PATH = DATA_DIR / "mofin.db"
+XIAOGUO_API = "http://192.168.1.122:18003/v1/chat/completions"
+XIAOGUO_MODEL = "Qwen3.6-27B-MTPLX-Optimized-Speed"
+XIAOGUO_TIMEOUT = 60
+
+
+def get_conn():
+    import sqlite3
+    conn = sqlite3.connect(str(DB_PATH))
+    conn.row_factory = sqlite3.Row
+    return conn
+
+
+def search_akshare_news(code, max_results=3):
+    """用 akshare 搜个股新闻"""
+    titles = []
+    if not HAS_AKSHARE:
+        return titles
+    try:
+        for k in ['http_proxy', 'https_proxy', 'HTTP_PROXY', 'HTTPS_PROXY']:
+            os.environ.pop(k, None)
+        df = ak.stock_news_em(symbol=code)
+        for _, r in df.head(max_results).iterrows():
+            title = r.get('新闻标题', '')
+            if title and len(title) > 5:
+                titles.append({"title": title, "url": r.get('新闻链接', '')})
+    except:
+        pass
+    return titles
+
+
+def call_xiaoguo(articles_text, timeout=XIAOGUO_TIMEOUT):
+    """调小果 LLM 分析新闻情感"""
+    prompt = f"""分析以下新闻标题，对每篇给出情感分类和摘要，再加总体判断。
+
+新闻：
+{articles_text}
+
+JSON格式：
+{{"overall_sentiment":"利好|利空|中性","summary":"总体判断","articles":[{{"title":"","sentiment":"","summary":"","reason":""}}]}}"""
+
+    payload = json.dumps({
+        "model": XIAOGUO_MODEL,
+        "messages": [
+            {"role": "system", "content": "你只输出JSON。"},
+            {"role": "user", "content": prompt}
+        ],
+        "temperature": 0.1,
+        "max_tokens": 2000,
+    }).encode()
+
+    opener = urllib.request.build_opener(urllib.request.ProxyHandler({}))
+    req = urllib.request.Request(
+        XIAOGUO_API, data=payload,
+        headers={"Content-Type": "application/json"},
+        method="POST"
+    )
+    try:
+        resp = opener.open(req, timeout=timeout)
+        result = json.loads(resp.read())
+        content = result["choices"][0]["message"]["content"]
+        # 从末尾提取完整JSON
+        depth = 0
+        start = -1
+        end = len(content)
+        for i in range(len(content) - 1, -1, -1):
+            if content[i] == "}":
+                if depth == 0:
+                    end = i + 1
+                depth += 1
+            elif content[i] == "{":
+                depth -= 1
+                if depth == 0:
+                    start = i
+                    break
+        if start >= 0:
+            return json.loads(content[start:end])
+    except Exception as e:
+        print(f"  小果调用失败: {e}", flush=True)
+    return None
+
+
+def main():
+    conn = get_conn()
+
+    # 读未处理的 signals（每次1条）
+    signals = conn.execute(
+        "SELECT * FROM sector_signals WHERE processed = 0 ORDER BY severity DESC, id ASC LIMIT 1"
+    ).fetchall()
+
+    if not signals:
+        print("无未处理的信号", flush=True)
+        conn.close()
+        return
+
+    signal = dict(signals[0])
+    print(f"处理信号: [{signal['severity']}] {signal['signal_type']} {signal['sector']}", flush=True)
+
+    # 从信号中提取需要搜索的股票代码
+    sector = signal["sector"]
+    related = json.loads(signal["related_stocks"] or "[]")
+    holdings = json.loads(signal["holdings_in_sector"] or "[]")
+    watchlist = json.loads(signal["watchlist_in_sector"] or "[]")
+
+    # 收集所有要搜的股票代码
+    codes_to_search = []
+    for item in related + holdings + watchlist:
+        code = item.get("code", "")
+        if code and code not in [c["code"] for c in codes_to_search]:
+            codes_to_search.append(item)
+
+    # 如果 stock_sectors 表中有成分股数据，也搜一下
+    members = conn.execute(
+        "SELECT s.code, s.name FROM stocks s "
+        "JOIN stock_sectors ss ON s.code = ss.code "
+        "WHERE ss.sector_name = ? LIMIT 5", (sector,)
+    ).fetchall()
+    for m in members:
+        if not any(c.get("code") == m["code"] for c in codes_to_search):
+            codes_to_search.append({"code": m["code"], "name": m["name"]})
+
+    # 搜新闻
+    all_articles = []
+    for item in codes_to_search:
+        code = item.get("code", "")
+        name = item.get("name", "")
+        if code:
+            articles = search_akshare_news(code, 3)
+            for a in articles:
+                if a["title"] not in [x["title"] for x in all_articles]:
+                    all_articles.append(a)
+            print(f"  搜 {name}({code}): {len(articles)} 篇", flush=True)
+
+    if not all_articles:
+        print(f"  未搜到相关新闻", flush=True)
+        conn.execute("UPDATE sector_signals SET processed = 1 WHERE id = ?", (signal["id"],))
+        conn.commit()
+        conn.close()
+        return
+
+    print(f"  共搜到 {len(all_articles)} 篇新闻，取前8篇分析", flush=True)
+
+    # 只取前8篇，避免小果LLM处理超时
+    batch = all_articles[:8]
+
+    # 调小果LLM分析
+    articles_text = "\n".join([f"{i+1}. {a['title']}" for i, a in enumerate(batch)])
+    result = call_xiaoguo(articles_text)
+
+    if not result:
+        print("  小果分析失败", flush=True)
+        conn.close()
+        return
+
+    # 写入 signal_news
+    searched_names = list(set([c.get("name", "") for c in codes_to_search if c.get("name")]))
+    conn.execute("""
+        INSERT INTO signal_news
+        (signal_id, sector, overall_sentiment, summary, key_articles, searched_stocks)
+        VALUES (?, ?, ?, ?, ?, ?)
+    """, (
+        signal["id"], sector,
+        result.get("overall_sentiment", "中性"),
+        result.get("summary", ""),
+        json.dumps(result.get("articles", []), ensure_ascii=False),
+        json.dumps(searched_names, ensure_ascii=False),
+    ))
+    conn.execute("UPDATE sector_signals SET processed = 1 WHERE id = ?", (signal["id"],))
+    conn.commit()
+
+    print(f"  完成: {result.get('overall_sentiment', '?')} — {str(result.get('summary', ''))[:80]}", flush=True)
+    conn.close()
+
+
+if __name__ == "__main__":
+    main()