feat: dividend-investing 迁移脚本到 skill 仓库

【背景】之前 dividend_alert.py 和 shell wrapper 在 ~/.hermes/scripts/ (本地) 不在 skill 仓库, SKILL.md 用 external: 引用. 修改不版本化. 【迁移】 - scripts/dividend_alert.py (13333 bytes) - scripts/dividend_alert_cn_hk.sh (proxychains4 + 过滤日志) - scripts/dividend_alert_us.sh - 删 ~/.hermes/scripts/* 三份旧副本 - cron jobs.json script 路径更新到 skill 仓库绝对路径 - 789a7710b1cf (A股+港股) → .../dividend-investing/scripts/dividend_alert_cn_hk.sh - 366934c1474c (美股) → .../dividend-investing/scripts/dividend_alert_us.sh 【SKILL.md 更新】 - scripts 段从 'external' 改为正常引用 - 路径从绝对 ~/.hermes/scripts 改为相对 scripts/ 【测试】cn_hk 脚本从新位置跑, 输出正确 (A股: 6 港股: 2), 无 [proxychains] 日志
2026-07-24 11:17:52 +08:00
parent 8b70ce3048
commit cb752eeb88
4 changed files with 383 additions and 3 deletions
@@ -10,14 +10,13 @@ metadata:
    tags: [trading, dividends, stocks, a-shares, hk-stocks, us-stocks, cron, dividend-stability]
    related_skills: [tonghuashun, longbridge-python-sdk, stock-analysis]
 scripts:
-  - scripts/dividend_alert.py: "python3 ~/.hermes/scripts/dividend_alert.py — daily cron job; runs via cronjob no_agent=true (script output delivered verbatim)"
-  - scripts/stability_scorer.py: "score_dividend_stability(symbol, market) → dict (years/CAGR/volatility → 0-100). Used by dividend_alert to label each A-share with stability stars."
+  - "scripts/dividend_alert.py: 'Daily dividend scan. Cron jobs (id `789a7710b1cf` A股+港股, `366934c1474c` 美股) call `scripts/dividend_alert_cn_hk.sh` and `scripts/dividend_alert_us.sh` (proxychains4 + 过滤 [proxychains] 日志). Contains score_dividend_stability() with _stability_cache per symbol per run. Edit here in skill repo to update.'"
 references:
  - dividend-yield-rate-sort: "分红扫描按股息率% 倒序(用户偏好 2026-07-13)"
  - fill-gap-timing: "填权时间线数据 + 抓取分析"
  - dividend-yield-arbitrage: "股息率 vs 融资成本套息"
  - cron-schedule-and-push-timing: "cron schedule / Beijing-time push timing (why 11:00 BJT)"
-  - dividend-stability-score: "5 维评分 (派息年数/CAGR/波动/最近/连续) 综合稳定性 0-100 + 5 星等级"
+  - dividend-stability-score: "5 维评分 (派息年数/CAGR/波动/最近/连续) 综合稳定性 0-100 + 5 星等级; 数据源 akshare stock_history_dividend_detail(indicator='分红'); 缓存避免重复查询; 2026-07-22 新增"
 requires:
  - python3 + akshare (pip install akshare)
  - python3 + requests (stdlib)
@@ -0,0 +1,357 @@
+#!/usr/bin/env python3
+"""
+股息登记日前一天提醒 — 纯 LongPort 版
+用 LongPort 同时查价格和行情，美股走 Nasdaq API。
+"""
+import os, sys, json, re, time
+from datetime import datetime, timedelta
+import requests
+import pandas as pd
+
+# 关掉长桥走 SOCKS 代理 (历史 bug)
+for k in ['http_proxy','https_proxy','HTTP_PROXY','HTTPS_PROXY']:
+    os.environ.pop(k, None)
+import requests
+
+BJ_TZ = timedelta(hours=8)
+HEADERS = {'User-Agent':'Mozilla/5.0'}
+
+def bj_now():
+    return datetime.utcnow() + BJ_TZ
+def next_trading_day(d):
+    while d.weekday() >= 5:
+        d += timedelta(days=1)
+    return d
+
+# ─── LongPort 初始化 ───
+# 2026-07-21 改用 longport_http module 替代 SDK (WSS 不稳定)
+# batch_quote 直接调 longport_http.get_quotes, 不再依赖 SDK
+_lp = True  # 占位兼容旧代码
+def get_lp():
+    """始终返回 True (longport_http module 替代 SDK)"""
+    return True
+
+# ─── A股 + 港股: AKShare 百度除权数据 ───
+def fetch_ah(target_date):
+    import akshare as ak
+    ds = target_date.strftime('%Y%m%d')
+    time.sleep(0.5)
+    try:
+        df = ak.news_trade_notify_dividend_baidu(date=ds)
+        res = []
+        for _, row in df.iterrows():
+            code = str(row['股票代码']).strip()
+            dr = str(row.get('分红','') or '').strip()
+            xch = str(row.get('交易所','') or '').strip()
+            name = str(row.get('股票简称','') or '').strip()
+            val = 0.0
+            if dr:
+                dr = dr.replace(',','')
+                nums = re.findall(r'[\d.]+', dr)
+                if nums: val = float(nums[0])
+            if val <= 0: continue
+            mkt = 'A' if xch != 'HK' else 'HK'
+            if xch == 'BJ': mkt = 'BJ'
+            res.append({'code':code,'name':name,'market':mkt,'div':val})
+        return res
+    except Exception as e:
+        return [{'error':str(e)}]
+
+# ─── 美股除权: Nasdaq API ───
+def fetch_us(target_date):
+    ds = target_date.strftime('%Y-%m-%d')
+    try:
+        r = requests.get(f'https://api.nasdaq.com/api/calendar/dividends?date={ds}',
+                         headers=HEADERS, timeout=15)
+        rows = r.json().get('data',{}).get('calendar',{}).get('rows',[])
+        res = []
+        for row in rows:
+            sym = row.get('symbol','').strip()
+            rate = float(row.get('dividend_Rate',0) or 0)
+            ann = float(row.get('indicated_Annual_Dividend',0) or 0)
+            rec = row.get('record_Date', row.get('dividend_Ex_Date','')).strip()
+            if rate <= 0: continue
+            res.append({'code':sym,'market':'US','div':rate,'ann':ann,'rec':rec})
+        return res
+    except Exception as e:
+        print(f"[WARN] fetch_us failed: {e}")
+        return []
+
+# ─── 价格查询（全走 LongPort） ───
+def map_a(code):
+    """603733 → 603733.SH"""
+    n = int(code) if code.isdigit() else 0
+    if 500000 <= n <= 689999: return f"{code}.SH"
+    if 0 <= n <= 399999: return f"{code}.SZ"
+    return f"{code}.BJ"
+
+def map_hk(code):
+    """01088 → 01088.HK"""
+    try: return f"{int(code):05d}.HK"
+    except: return f"{code}.HK"
+
+def batch_quote(symbols):
+    """Batch quote via longport_http (HTTP, 替代 longport SDK WSS)"""
+    if not symbols:
+        return {}
+    try:
+        # 2026-07-21 改用 longport_http module (避免 WSS 不稳定)
+        import sys
+        sys.path.insert(0, '/home/openclaw/.hermes/scripts')
+        from longport_http import get_quotes
+        quotes = get_quotes(symbols)
+        # 返回 {symbol: price} 格式 (兼容旧代码)
+        return {sym: q['price'] for sym, q in quotes.items()}
+    except Exception:
+        return {}
+
+# ─── 分红稳定性评分 ───
+_stability_cache = {}  # symbol -> dict (避免重复 akshare 调用)
+
+def score_dividend_stability(symbol: str, market: str) -> dict:
+    """
+    评分: 派息年数 + 派息增长 + 波动率 → 0-100 分
+    返回: {"score": 75, "level": 4, "years": 10, "cagr": 5.2, "volatility": 0.3, "label": "基本稳定"}
+    """
+    cache_key = f"{market}:{symbol}"
+    if cache_key in _stability_cache:
+        return _stability_cache[cache_key]
+    try:
+        if market != "CN":
+            return None  # 暂时只支持 A 股 (akshare)
+
+        import akshare as ak
+        # 拿历史派息
+        if market == "CN":
+            code = symbol.replace(".SH", "").replace(".SZ", "").replace(".BJ", "")
+            df = ak.stock_history_dividend_detail(symbol=code, indicator="分红")
+        if df is None or len(df) < 3:
+            _stability_cache[cache_key] = None
+            return None
+
+        # 只取"实施"过(排除预案/未实施)
+        df = df[df["进度"] == "实施"].copy()
+        df["派息"] = pd.to_numeric(df["派息"], errors="coerce")
+        df = df.dropna(subset=["派息"])
+        df = df[df["派息"] > 0]  # 排除 0 派息
+        if len(df) < 3:
+            return None
+
+        # 排序(新→旧)
+        df["年份"] = pd.to_datetime(df["公告日期"]).dt.year
+        df = df.sort_values("年份", ascending=False).reset_index(drop=True)
+        years_count = df["年份"].nunique()
+        latest_div = df["派息"].iloc[0]
+        oldest_div = df["派息"].iloc[-1]
+
+        # 1. 派息年数 (30分)
+        years_score = min(30, years_count * 2)  # 15 年封顶 30 分
+
+        # 2. 派息 CAGR (20分) - 复合年增长
+        if years_count >= 2 and oldest_div > 0:
+            cagr = (latest_div / oldest_div) ** (1 / (years_count - 1)) - 1
+            if cagr >= 0.10:
+                cagr_score = 20
+            elif cagr >= 0.05:
+                cagr_score = 15
+            elif cagr >= 0.02:
+                cagr_score = 10
+            elif cagr >= 0:
+                cagr_score = 5
+            else:
+                cagr_score = 0
+        else:
+            cagr = 0
+            cagr_score = 0
+
+        # 3. 波动率 (25分) - 派息变异系数 (std/mean)
+        if len(df) >= 3:
+            mean_div = df["派息"].mean()
+            std_div = df["派息"].std()
+            cv = std_div / mean_div if mean_div > 0 else 1
+            if cv <= 0.2:
+                vol_score = 25
+            elif cv <= 0.4:
+                vol_score = 20
+            elif cv <= 0.6:
+                vol_score = 15
+            elif cv <= 0.8:
+                vol_score = 10
+            else:
+                vol_score = 5
+        else:
+            cv = 1
+            vol_score = 5
+
+        # 4. 最近派息正向 (15分) - 最新 ≥ 上一次
+        if len(df) >= 2 and df["派息"].iloc[0] >= df["派息"].iloc[1]:
+            recent_score = 15
+        else:
+            recent_score = 5
+
+        # 5. 连续性 (10分) - 最近 3 年都派
+        if years_count >= 3 and len(df["年份"].head(3).unique()) >= 3:
+            consecutive_score = 10
+        else:
+            consecutive_score = 0
+
+        total = years_score + cagr_score + vol_score + recent_score + consecutive_score
+        # 等级
+        if total >= 80:
+            level, label = 5, "长期稳定"
+        elif total >= 60:
+            level, label = 4, "基本稳定"
+        elif total >= 40:
+            level, label = 3, "不稳定"
+        elif total >= 20:
+            level, label = 2, "风险大"
+        else:
+            level, label = 1, "不推荐"
+
+        return {
+            "score": total,
+            "level": level,
+            "label": label,
+            "years": years_count,
+            "cagr": cagr * 100,
+            "cv": cv,
+            "latest_div": latest_div,
+        }
+        _stability_cache[cache_key] = {
+            "score": total,
+            "level": level,
+            "label": label,
+            "years": years_count,
+            "cagr": cagr * 100,
+            "cv": cv,
+            "latest_div": latest_div,
+        }
+        return _stability_cache[cache_key]
+    except Exception as e:
+        print(f"  [WARN] score_dividend_stability {symbol} failed: {e}", file=sys.stderr)
+        _stability_cache[cache_key] = None
+        return None
+
+
+# ─── 格式化 ───
+def fmt(a_h, hk_h, us_h, a_p, hk_p, us_p):
+    now = bj_now()
+    tomorrow = next_trading_day(now + timedelta(days=1))
+    wd = ['周一','周二','周三','周四','周五','周六','周日'][tomorrow.weekday()]
+    L = ['', '📢 明日除权·红利提醒', '━'*24,
+         f'📅 今日 {now.strftime("%Y-%m-%d")} 推送',
+         f'⏰ 明天 {tomorrow.strftime("%Y-%m-%d")} ({wd}) 除权除息',
+         '💡 明天是登记日，今天买入仍享分红', '']
+    has = False
+
+    if a_h:
+        has = True; L += ['─'*24, '🇨🇳 A股 明日除权 TOP', '']
+        for r in a_h[:12]:
+            d,c,n = r['div'],r['code'],r['name']
+            star = '⭐' if d>=10 else '💎' if d>=5 else ''
+            p = a_p.get(f"{c}.SH") or a_p.get(f"{c}.SZ") or a_p.get(f"{c}.BJ")
+            y = f' | 股息率 {d/10/p*100:.2f}%' if p and p>0 else ''
+            # 2026-07-22 加分红稳定性评分
+            stab = score_dividend_stability(c, "CN")
+            stab_tag = f' [{stab["level"]}★{stab["label"]} {stab["years"]}年CAGR{stab["cagr"]:+.0f}%]' if stab else ''
+            L += [f'  {star}{c} {n}{stab_tag}', f'    💰每10股派{d:.2f}元 | 📊{p if p else "N/A"}{y}', '']
+
+    if hk_h:
+        has = True; L += ['─'*24, '🇭🇰 港股 明日除权 TOP', '']
+        for r in hk_h[:8]:
+            d,c,n = r['div'],r['code'],r['name']
+            lp = f"{int(c):05d}.HK"
+            p = hk_p.get(lp)
+            y = f' | 股息率 {d/10/p*100:.2f}%' if p and p>0 else ''
+            L += [f'  {c} {n}', f'    💰每10股派{d:.2f}港元 | 📊HKD {p if p else "N/A"}{y}', '']
+
+    if us_h:
+        has = True; L += ['─'*24, '🇺🇸 美股 明日除权 TOP', '']
+        for r in us_h[:8]:
+            d,c = r['div'],r['code']
+            ann = r.get('ann',0)
+            rec = r.get('rec','')
+            p = us_p.get(f"{c}.US")
+            y = f' | 股息率 {ann/p*100:.2f}%' if p and p>0 and ann>0 else ''
+            L += [f'  {c}', f'    💰${d:.2f}/股 | 年化${ann:.2f} | {ann/d:.0f}次/年']
+            if p: L += [f'    📊${p:.2f}{y}']
+            L += [f'    📅登记日{rec}', '']
+
+    if not has: L += ['✅ 明天没有高息股票除权，休息一天~', '']
+    L += ['━'*24, '📌 操作提示',
+          '• 今天买入 → 明天登记 → 拿分红',
+          '• A股持股>1年免税，<1月20%税',
+          '━'*24, '🤖 Hermes 每日红利雷达']
+    return '\n'.join(L)
+
+def main():
+    import argparse
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--market', default='all',
+                        choices=['all', 'cn_hk', 'us'],
+                        help='all = A+HK+US, cn_hk = A股+港股, us = 美股')
+    args = parser.parse_args()
+
+    now = bj_now()
+    tomorrow = next_trading_day(now + timedelta(days=1))
+    print(f'[Div] {now.strftime("%Y-%m-%d")} - ex-div {tomorrow.strftime("%Y-%m-%d")} market={args.market}')
+
+    # 1. A+H除权数据
+    a_r, hk_r = [], []
+    if args.market in ('all', 'cn_hk'):
+        ah = fetch_ah(tomorrow)
+        a_r = [r for r in ah if r.get('market') in ('A','BJ')]
+        hk_r = [r for r in ah if r.get('market')=='HK']
+        print(f'  A股: {len(a_r)} 港股: {len(hk_r)}')
+
+    # 2. 美股除权
+    us_r = []
+    if args.market in ('all', 'us'):
+        us_r = fetch_us(tomorrow)
+        print(f'  美股: {len(us_r)}')
+
+    # 3. 临时按 div 排序 (占位), 后面 batch_quote 拿到价后会重新按股息率排序
+    a_h = sorted(a_r, key=lambda x: -x['div'])
+    hk_h = sorted(hk_r, key=lambda x: -x['div'])
+    us_h = sorted(us_r, key=lambda x: -x['div'])
+
+    # 4. 批量查价
+    a_syms = [map_a(r['code']) for r in a_h[:15]] if a_h else []
+    hk_syms = [map_hk(r['code']) for r in hk_h[:10]] if hk_h else []
+    us_syms = [f"{r['code']}.US" for r in us_h[:10]] if us_h else []
+
+    all_syms = a_syms + hk_syms + us_syms
+    if not get_lp():
+        print("[WARN] LongPort not available")
+    
+    p_all = batch_quote(all_syms) if get_lp() else {}
+    # Split prices by market
+    a_p = {k:v for k,v in p_all.items() if k.endswith(('.SH','.SZ','.BJ'))}
+    hk_p = {k:v for k,v in p_all.items() if k.endswith('.HK')}
+    us_p = {k:v for k,v in p_all.items() if k.endswith('.US')}
+
+    # 4.5. 重排序 - 按股息率% 倒序 (派息 / 当前价 × 100), 越高越排前
+    def _yr_a(r):
+        price = (a_p.get(r['code'] + '.SH') or a_p.get(r['code'] + '.SZ') or a_p.get(r['code'] + '.BJ') or 0)
+        if price <= 0: return 0
+        return (r.get('div', 0) / 10) / price * 100
+    def _yr_hk(r):
+        price = (hk_p.get(r['code'] + '.HK') or 0)
+        if price <= 0: return 0
+        return (r.get('div', 0) / 10) / price * 100
+    def _yr_us(r):
+        price = (us_p.get(r['code'] + '.US') or 0)
+        if price <= 0: return 0
+        # fetch_us 字段名是 'ann' (不是 'ann_div'), 单次派息是 'div'
+        ann = r.get('ann', 0) or r.get('div', 0)
+        return ann / price * 100
+
+    if a_p: a_h = sorted(a_h, key=lambda x: -_yr_a(x))
+    if hk_p: hk_h = sorted(hk_h, key=lambda x: -_yr_hk(x))
+    if us_p: us_h = sorted(us_h, key=lambda x: -_yr_us(x))
+
+    # 5. 输出
+    print('\n' + fmt(a_h, hk_h, us_h, a_p, hk_p, us_p))
+
+if __name__ == '__main__':
+    main()
@@ -0,0 +1,12 @@
+#!/bin/bash
+# 股息扫描 - A股 + 港股 (北京时间 11:00 跑)
+# 用于 cron '股息登记日前一天提醒 - A股港股' (11:00 北京时间)
+export LONGBRIDGE_HTTP_URL=https://openapi.longbridge.com
+export LONGBRIDGE_REGION=ap
+export LONGBRIDGE_TRADE_ENABLED=true
+export PROXYCHAINS_CONF=/home/openclaw/.proxychains/proxychains.conf
+
+# 跑 + 过滤 proxychains 调试日志 (保留正常输出)
+proxychains4 -f ~/.proxychains/proxychains.conf \
+  python3 $(dirname $0)/dividend_alert.py --market cn_hk 2>&1 \
+  | grep -v '^\[proxychains\]'
@@ -0,0 +1,12 @@
+#!/bin/bash
+# 股息扫描 - 美股 (北京时间 21:00 跑, 美股开盘前 30 min)
+# 用于 cron '股息登记日前一天提醒 - 美股' (21:00 北京时间)
+export LONGBRIDGE_HTTP_URL=https://openapi.longbridge.com
+export LONGBRIDGE_REGION=ap
+export LONGBRIDGE_TRADE_ENABLED=true
+export PROXYCHAINS_CONF=/home/openclaw/.proxychains/proxychains.conf
+
+# 跑 + 过滤 proxychains 调试日志
+proxychains4 -f ~/.proxychains/proxychains.conf \
+  python3 $(dirname $0)/dividend_alert.py --market us 2>&1 \
+  | grep -v '^\[proxychains\]'