mike
cb752eeb88
【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
358 lines
13 KiB
Python
358 lines
13 KiB
Python
#!/usr/bin/env python3
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"""
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股息登记日前一天提醒 — 纯 LongPort 版
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用 LongPort 同时查价格和行情，美股走 Nasdaq API。
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"""
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import os, sys, json, re, time
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from datetime import datetime, timedelta
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import requests
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import pandas as pd
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# 关掉长桥走 SOCKS 代理 (历史 bug)
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for k in ['http_proxy','https_proxy','HTTP_PROXY','HTTPS_PROXY']:
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os.environ.pop(k, None)
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import requests
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BJ_TZ = timedelta(hours=8)
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HEADERS = {'User-Agent':'Mozilla/5.0'}
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def bj_now():
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return datetime.utcnow() + BJ_TZ
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def next_trading_day(d):
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while d.weekday() >= 5:
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d += timedelta(days=1)
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return d
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# ─── LongPort 初始化 ───
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# 2026-07-21 改用 longport_http module 替代 SDK (WSS 不稳定)
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# batch_quote 直接调 longport_http.get_quotes, 不再依赖 SDK
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_lp = True # 占位兼容旧代码
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def get_lp():
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"""始终返回 True (longport_http module 替代 SDK)"""
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return True
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# ─── A股 + 港股: AKShare 百度除权数据 ───
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def fetch_ah(target_date):
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import akshare as ak
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ds = target_date.strftime('%Y%m%d')
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time.sleep(0.5)
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try:
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df = ak.news_trade_notify_dividend_baidu(date=ds)
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res = []
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for _, row in df.iterrows():
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code = str(row['股票代码']).strip()
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dr = str(row.get('分红','') or '').strip()
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xch = str(row.get('交易所','') or '').strip()
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name = str(row.get('股票简称','') or '').strip()
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val = 0.0
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if dr:
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dr = dr.replace(',','')
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nums = re.findall(r'[\d.]+', dr)
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if nums: val = float(nums[0])
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if val <= 0: continue
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mkt = 'A' if xch != 'HK' else 'HK'
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if xch == 'BJ': mkt = 'BJ'
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res.append({'code':code,'name':name,'market':mkt,'div':val})
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return res
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except Exception as e:
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return [{'error':str(e)}]
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# ─── 美股除权: Nasdaq API ───
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def fetch_us(target_date):
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ds = target_date.strftime('%Y-%m-%d')
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try:
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r = requests.get(f'https://api.nasdaq.com/api/calendar/dividends?date={ds}',
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headers=HEADERS, timeout=15)
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rows = r.json().get('data',{}).get('calendar',{}).get('rows',[])
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res = []
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for row in rows:
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sym = row.get('symbol','').strip()
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rate = float(row.get('dividend_Rate',0) or 0)
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ann = float(row.get('indicated_Annual_Dividend',0) or 0)
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rec = row.get('record_Date', row.get('dividend_Ex_Date','')).strip()
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if rate <= 0: continue
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res.append({'code':sym,'market':'US','div':rate,'ann':ann,'rec':rec})
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return res
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except Exception as e:
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print(f"[WARN] fetch_us failed: {e}")
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return []
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# ─── 价格查询（全走 LongPort） ───
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def map_a(code):
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"""603733 → 603733.SH"""
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n = int(code) if code.isdigit() else 0
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if 500000 <= n <= 689999: return f"{code}.SH"
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if 0 <= n <= 399999: return f"{code}.SZ"
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return f"{code}.BJ"
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def map_hk(code):
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"""01088 → 01088.HK"""
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try: return f"{int(code):05d}.HK"
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except: return f"{code}.HK"
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def batch_quote(symbols):
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"""Batch quote via longport_http (HTTP, 替代 longport SDK WSS)"""
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if not symbols:
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return {}
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try:
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# 2026-07-21 改用 longport_http module (避免 WSS 不稳定)
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import sys
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sys.path.insert(0, '/home/openclaw/.hermes/scripts')
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from longport_http import get_quotes
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quotes = get_quotes(symbols)
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# 返回 {symbol: price} 格式 (兼容旧代码)
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return {sym: q['price'] for sym, q in quotes.items()}
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except Exception:
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return {}
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# ─── 分红稳定性评分 ───
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_stability_cache = {} # symbol -> dict (避免重复 akshare 调用)
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def score_dividend_stability(symbol: str, market: str) -> dict:
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"""
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评分: 派息年数 + 派息增长 + 波动率 → 0-100 分
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返回: {"score": 75, "level": 4, "years": 10, "cagr": 5.2, "volatility": 0.3, "label": "基本稳定"}
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"""
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cache_key = f"{market}:{symbol}"
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if cache_key in _stability_cache:
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return _stability_cache[cache_key]
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try:
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if market != "CN":
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return None # 暂时只支持 A 股 (akshare)
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import akshare as ak
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# 拿历史派息
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if market == "CN":
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code = symbol.replace(".SH", "").replace(".SZ", "").replace(".BJ", "")
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df = ak.stock_history_dividend_detail(symbol=code, indicator="分红")
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if df is None or len(df) < 3:
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_stability_cache[cache_key] = None
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return None
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# 只取"实施"过(排除预案/未实施)
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df = df[df["进度"] == "实施"].copy()
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df["派息"] = pd.to_numeric(df["派息"], errors="coerce")
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df = df.dropna(subset=["派息"])
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df = df[df["派息"] > 0] # 排除 0 派息
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if len(df) < 3:
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return None
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# 排序(新→旧)
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df["年份"] = pd.to_datetime(df["公告日期"]).dt.year
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df = df.sort_values("年份", ascending=False).reset_index(drop=True)
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years_count = df["年份"].nunique()
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latest_div = df["派息"].iloc[0]
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oldest_div = df["派息"].iloc[-1]
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# 1. 派息年数 (30分)
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years_score = min(30, years_count * 2) # 15 年封顶 30 分
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# 2. 派息 CAGR (20分) - 复合年增长
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if years_count >= 2 and oldest_div > 0:
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cagr = (latest_div / oldest_div) ** (1 / (years_count - 1)) - 1
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if cagr >= 0.10:
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cagr_score = 20
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elif cagr >= 0.05:
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cagr_score = 15
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elif cagr >= 0.02:
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cagr_score = 10
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elif cagr >= 0:
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cagr_score = 5
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else:
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cagr_score = 0
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else:
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cagr = 0
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cagr_score = 0
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# 3. 波动率 (25分) - 派息变异系数 (std/mean)
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if len(df) >= 3:
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mean_div = df["派息"].mean()
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std_div = df["派息"].std()
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cv = std_div / mean_div if mean_div > 0 else 1
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if cv <= 0.2:
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vol_score = 25
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elif cv <= 0.4:
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vol_score = 20
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elif cv <= 0.6:
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vol_score = 15
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elif cv <= 0.8:
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vol_score = 10
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else:
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vol_score = 5
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else:
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cv = 1
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vol_score = 5
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# 4. 最近派息正向 (15分) - 最新 ≥ 上一次
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if len(df) >= 2 and df["派息"].iloc[0] >= df["派息"].iloc[1]:
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recent_score = 15
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else:
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recent_score = 5
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# 5. 连续性 (10分) - 最近 3 年都派
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if years_count >= 3 and len(df["年份"].head(3).unique()) >= 3:
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consecutive_score = 10
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else:
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consecutive_score = 0
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total = years_score + cagr_score + vol_score + recent_score + consecutive_score
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# 等级
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if total >= 80:
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level, label = 5, "长期稳定"
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elif total >= 60:
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level, label = 4, "基本稳定"
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elif total >= 40:
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level, label = 3, "不稳定"
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elif total >= 20:
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level, label = 2, "风险大"
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else:
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level, label = 1, "不推荐"
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return {
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"score": total,
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"level": level,
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"label": label,
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"years": years_count,
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"cagr": cagr * 100,
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"cv": cv,
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"latest_div": latest_div,
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}
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_stability_cache[cache_key] = {
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"score": total,
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"level": level,
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"label": label,
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"years": years_count,
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"cagr": cagr * 100,
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"cv": cv,
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"latest_div": latest_div,
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}
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return _stability_cache[cache_key]
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except Exception as e:
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print(f" [WARN] score_dividend_stability {symbol} failed: {e}", file=sys.stderr)
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_stability_cache[cache_key] = None
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return None
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# ─── 格式化 ───
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def fmt(a_h, hk_h, us_h, a_p, hk_p, us_p):
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now = bj_now()
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tomorrow = next_trading_day(now + timedelta(days=1))
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wd = ['周一','周二','周三','周四','周五','周六','周日'][tomorrow.weekday()]
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L = ['', '📢 明日除权·红利提醒', '━'*24,
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f'📅 今日 {now.strftime("%Y-%m-%d")} 推送',
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f'⏰ 明天 {tomorrow.strftime("%Y-%m-%d")} ({wd}) 除权除息',
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'💡 明天是登记日，今天买入仍享分红', '']
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has = False
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if a_h:
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has = True; L += ['─'*24, '🇨🇳 A股 明日除权 TOP', '']
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for r in a_h[:12]:
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d,c,n = r['div'],r['code'],r['name']
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star = '⭐' if d>=10 else '💎' if d>=5 else ''
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p = a_p.get(f"{c}.SH") or a_p.get(f"{c}.SZ") or a_p.get(f"{c}.BJ")
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y = f' | 股息率 {d/10/p*100:.2f}%' if p and p>0 else ''
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# 2026-07-22 加分红稳定性评分
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stab = score_dividend_stability(c, "CN")
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stab_tag = f' [{stab["level"]}★{stab["label"]} {stab["years"]}年CAGR{stab["cagr"]:+.0f}%]' if stab else ''
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L += [f' {star}{c} {n}{stab_tag}', f' 💰每10股派{d:.2f}元 | 📊{p if p else "N/A"}{y}', '']
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if hk_h:
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has = True; L += ['─'*24, '🇭🇰 港股 明日除权 TOP', '']
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for r in hk_h[:8]:
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d,c,n = r['div'],r['code'],r['name']
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lp = f"{int(c):05d}.HK"
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p = hk_p.get(lp)
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y = f' | 股息率 {d/10/p*100:.2f}%' if p and p>0 else ''
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L += [f' {c} {n}', f' 💰每10股派{d:.2f}港元 | 📊HKD {p if p else "N/A"}{y}', '']
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if us_h:
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has = True; L += ['─'*24, '🇺🇸 美股 明日除权 TOP', '']
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for r in us_h[:8]:
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d,c = r['div'],r['code']
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ann = r.get('ann',0)
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rec = r.get('rec','')
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p = us_p.get(f"{c}.US")
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y = f' | 股息率 {ann/p*100:.2f}%' if p and p>0 and ann>0 else ''
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L += [f' {c}', f' 💰${d:.2f}/股 | 年化${ann:.2f} | {ann/d:.0f}次/年']
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if p: L += [f' 📊${p:.2f}{y}']
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L += [f' 📅登记日{rec}', '']
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if not has: L += ['✅ 明天没有高息股票除权，休息一天~', '']
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L += ['━'*24, '📌 操作提示',
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'• 今天买入 → 明天登记 → 拿分红',
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'• A股持股>1年免税，<1月20%税',
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'━'*24, '🤖 Hermes 每日红利雷达']
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return '\n'.join(L)
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def main():
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import argparse
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parser = argparse.ArgumentParser()
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parser.add_argument('--market', default='all',
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choices=['all', 'cn_hk', 'us'],
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help='all = A+HK+US, cn_hk = A股+港股, us = 美股')
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args = parser.parse_args()
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now = bj_now()
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tomorrow = next_trading_day(now + timedelta(days=1))
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print(f'[Div] {now.strftime("%Y-%m-%d")} - ex-div {tomorrow.strftime("%Y-%m-%d")} market={args.market}')
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# 1. A+H除权数据
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a_r, hk_r = [], []
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if args.market in ('all', 'cn_hk'):
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ah = fetch_ah(tomorrow)
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a_r = [r for r in ah if r.get('market') in ('A','BJ')]
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hk_r = [r for r in ah if r.get('market')=='HK']
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print(f' A股: {len(a_r)} 港股: {len(hk_r)}')
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# 2. 美股除权
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us_r = []
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if args.market in ('all', 'us'):
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us_r = fetch_us(tomorrow)
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print(f' 美股: {len(us_r)}')
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# 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
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a_h = sorted(a_r, key=lambda x: -x['div'])
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hk_h = sorted(hk_r, key=lambda x: -x['div'])
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us_h = sorted(us_r, key=lambda x: -x['div'])
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# 4. 批量查价
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a_syms = [map_a(r['code']) for r in a_h[:15]] if a_h else []
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hk_syms = [map_hk(r['code']) for r in hk_h[:10]] if hk_h else []
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us_syms = [f"{r['code']}.US" for r in us_h[:10]] if us_h else []
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all_syms = a_syms + hk_syms + us_syms
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if not get_lp():
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print("[WARN] LongPort not available")
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p_all = batch_quote(all_syms) if get_lp() else {}
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# Split prices by market
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a_p = {k:v for k,v in p_all.items() if k.endswith(('.SH','.SZ','.BJ'))}
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hk_p = {k:v for k,v in p_all.items() if k.endswith('.HK')}
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us_p = {k:v for k,v in p_all.items() if k.endswith('.US')}
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# 4.5. 重排序 - 按股息率% 倒序 (派息 / 当前价 × 100), 越高越排前
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def _yr_a(r):
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price = (a_p.get(r['code'] + '.SH') or a_p.get(r['code'] + '.SZ') or a_p.get(r['code'] + '.BJ') or 0)
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if price <= 0: return 0
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return (r.get('div', 0) / 10) / price * 100
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def _yr_hk(r):
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price = (hk_p.get(r['code'] + '.HK') or 0)
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if price <= 0: return 0
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return (r.get('div', 0) / 10) / price * 100
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def _yr_us(r):
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price = (us_p.get(r['code'] + '.US') or 0)
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if price <= 0: return 0
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# fetch_us 字段名是 'ann' (不是 'ann_div'), 单次派息是 'div'
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ann = r.get('ann', 0) or r.get('div', 0)
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return ann / price * 100
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if a_p: a_h = sorted(a_h, key=lambda x: -_yr_a(x))
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if hk_p: hk_h = sorted(hk_h, key=lambda x: -_yr_hk(x))
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if us_p: us_h = sorted(us_h, key=lambda x: -_yr_us(x))
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# 5. 输出
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print('\n' + fmt(a_h, hk_h, us_h, a_p, hk_p, us_p))
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if __name__ == '__main__':
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main()
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