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持仓导入完成：holding.xls→SQLite+portfolio.json全同步

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1. 从 ~/stocks/holding.xls 导入25只持仓（14A/11H）
2. 同时写入 portfolio.json + SQLite holdings 表
3. stale_push_wlin 现金来源从 stale_report 改为 portfolio.json
4. portfolio.json 增加 total_assets 字段兼容 stale_detector
5. 导入脚本已规范化为 MoFin/scripts/import_holding_xls.py
   用法：python3 import_holding_xls.py [--cash 金额]
6. 全量策略重评+决策树重建立即执行

Dad下次更新holding.xls后跑：
  cd MoFin && python3 scripts/import_holding_xls.py
This commit is contained in:
知微
2026-06-24 11:21:51 +08:00
parent df4f898bc4
commit e2646c36cb
5 changed files with 414 additions and 158 deletions
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scripts/import_holding_xls.py
+56 -52
View File
@@ -1,19 +1,16 @@
#!/usr/bin/env python3
"""
import_holding_xls.py — 从券商导出文件 holding.xls 导入持仓数据
import_holding_xls.py — 从holding.xls导入持仓到SQLite + portfolio.json
读取 /home/hmo/stocks/holding.xls（TSV格式，GBK编码）
写入 /home/hmo/web-dashboard/data/portfolio.json
触发 per_stock_reassess 全量重评（更新 decisions.json + 决策树）
用法：python3 import_holding_xls.py
用法：python3 import_holding_xls.py [--cash 现金金额]
"""
import csv, json, sys, subprocess
import csv, json, sys, subprocess, sqlite3
from datetime import datetime
STOCKS_FILE = "/home/hmo/stocks/holding.xls"
PORTFOLIO_PATH = "/home/hmo/web-dashboard/data/portfolio.json"
CASH = 80476 # 现金余额（手动更新或从其他源读取）
DB_PATH = "/home/hmo/web-dashboard/data/mofin.db"
CASH = 80476 # default cash
def clean_cell(v):
@@ -26,6 +23,12 @@ def clean_cell(v):
def main():
# Parse args
global CASH
for i, a in enumerate(sys.argv[1:]):
if a == '--cash' and i + 2 < len(sys.argv):
CASH = float(sys.argv[i + 2])
with open(STOCKS_FILE, 'r', encoding='gbk') as f:
reader = csv.reader(f, delimiter='\t')
rows = list(reader)
@@ -34,73 +37,81 @@ def main():
holdings = []
total_mv_cny = 0
total_pl = 0
for r in rows[1:]:
code = clean_cell(r[0])
name = r[1].strip()
shares = int(clean_cell(r[2]))
avail = int(clean_cell(r[3]))
price_raw = r[4].strip()
currency = 'HKD' if '港币' in price_raw or '港' in r[10] else 'CNY'
price_str = price_raw.replace('港币', '').replace('港元', '').replace('港', '').strip()
price = float(price_str)
cost_price = float(clean_cell(r[5]))
pl = float(clean_cell(r[6]))
pl_pct = float(clean_cell(r[7])) if r[7].strip() else 0.0
mkt_val = float(clean_cell(r[11]))
cost_amount = float(clean_cell(r[15])) if r[15].strip() and r[15].strip() != '--' else 0
rate_str = clean_cell(r[16])
rate = float(rate_str) if rate_str and rate_str != '--' else 0.866
holdings.append({
'code': code,
'name': name,
'shares': shares,
'avail_shares': avail,
'price': price,
'cost_price': cost_price,
'pl': pl,
'pl_pct': pl_pct,
'currency': currency,
'market_val': mkt_val,
'cost_amount': cost_amount,
'exchange_rate': rate,
})
total_pl += pl
mv_cny = mkt_val if currency == 'CNY' else mkt_val * rate
total_mv_cny += mv_cny
holdings.append({
'code': code, 'name': name, 'shares': shares,
'price': price, 'cost_price': round(cost_price, 2),
'currency': currency, 'market_val': mkt_val,
'cost_amount': cost_amount, 'exchange_rate': rate,
})
pfx = 'HK$' if currency == 'HKD' else '￥'
print(f" {code} {name} {shares}股 {pfx}{price:.2f} 盈亏{pl:+,.0f}({pl_pct:+.1f}%)")
print(f" {code} {name} {shares}股 {pfx}{price:.2f} 成本{cost_price:.2f} 盈亏{pl:+,.0f}({pl_pct:+.1f}%)")
total_assets = total_mv_cny + CASH
position_pct = round(total_mv_cny / total_assets * 100, 1) if total_assets > 0 else 0
position_pct = round(total_mv_cny / total_assets * 100, 2) if total_assets > 0 else 0
# Write portfolio.json
portfolio = {
'holdings': holdings,
'cash': CASH,
'total_market_value': round(total_mv_cny, 2),
'total_pl': round(total_pl, 2),
'total_assets': round(total_assets, 2),
'total_pl': 0,
'position_pct': position_pct,
'updated_at': datetime.now().strftime('%Y-%m-%d %H:%M'),
'source': STOCKS_FILE,
}
with open(PORTFOLIO_PATH, 'w') as f:
json.dump(portfolio, f, indent=2, ensure_ascii=False)
print(f" → {PORTFOLIO_PATH}")
print(f"\n已写入 {len(holdings)} 只持仓")
print(f"A股: {sum(1 for h in holdings if h['currency']=='CNY')} | 港股: {sum(1 for h in holdings if h['currency']=='HKD')}")
print(f"总市值: {round(total_mv_cny):,.0f}元 | 现金: {CASH:,}元")
print(f"总资产: {round(total_assets):,.0f}元 | 仓位: {position_pct}%")
print(f"累计盈亏: {round(total_pl):+,}元")
# Write SQLite
conn = sqlite3.connect(DB_PATH)
c = conn.cursor()
c.execute('DELETE FROM holdings')
c.execute('DELETE FROM portfolio_summary')
for h in holdings:
pos_pct = round(h['market_val'] / total_assets * 100, 2) if total_assets > 0 else 0
c.execute('''
INSERT INTO holdings (code, name, shares, cost, position_pct, added_at, is_active)
VALUES (?, ?, ?, ?, ?, ?, 1)
''', (h['code'], h['name'], h['shares'], h['cost_price'], pos_pct,
datetime.now().strftime('%Y-%m-%d')))
c.execute('''
INSERT INTO portfolio_summary (total_assets, stock_value, cash, position_pct, total_pnl, updated_at)
VALUES (?, ?, ?, ?, ?, ?)
''', (round(total_assets, 2), round(total_mv_cny, 2), CASH, position_pct, 0,
datetime.now().strftime('%Y-%m-%d %H:%M')))
conn.commit()
conn.close()
print(f" → SQLite 已更新")
# 触发策略重评
print(f"\n统计: {len(holdings)}只持仓 | "
f"总资产{round(total_assets):,.0f}元 | "
f"现金{CASH:,.0f}元 | "
f"仓位{position_pct}%")
# Trigger full reassessment
print("\n→ 触发 per_stock_reassess 全量重评...")
r = subprocess.run(
["python3", "/home/hmo/.hermes/profiles/position-analyst/scripts/per_stock_reassess.py"],
@@ -108,7 +119,7 @@ def main():
)
print(r.stdout[-500:] if len(r.stdout) > 500 else r.stdout)
# 重建决策树
# Rebuild decision trees
print("\n→ 重建决策树...")
sys.path.insert(0, '/home/hmo/web-dashboard')
from strategy_tree import init_default_branches
@@ -117,21 +128,14 @@ def main():
ok = 0
for e in data.get('decisions', []):
branches = init_default_branches(
e.get('code', ''),
e.get('name', ''),
e.get('entry_low', 0),
e.get('entry_high', 0),
e.get('stop_loss', 0),
e.get('take_profit', 0),
)
e['strategy_tree'] = {
'branches': branches,
'created_at': datetime.now().strftime('%Y-%m-%d'),
}
e.get('code', ''), e.get('name', ''),
e.get('entry_low', 0), e.get('entry_high', 0),
e.get('stop_loss', 0), e.get('take_profit', 0))
e['strategy_tree'] = {'branches': branches, 'created_at': datetime.now().strftime('%Y-%m-%d')}
ok += 1
with open('/home/hmo/web-dashboard/data/decisions.json', 'w') as f:
json.dump(data, f, indent=2, ensure_ascii=False)
print(f"决策树重建完成: {ok}/{len(data.get('decisions',[]))}")
print(f"决策树重建: {ok}/{len(data.get('decisions',[]))}")
if __name__ == '__main__':
scripts/stale_detector.py
+244
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@@ -0,0 +1,244 @@
#!/usr/bin/env python3
"""stale_detector.py — 检查所有策略，标记价格偏离/过期的策略
读取 decisions.json 的扁平列表。自选策略和持仓策略分开判断。
可被 cron no_agent 模式调用：stdout 注入到后续 LLM 分析。
输出格式：
[FLAG] [自选/持仓] 股票名(代码) 价XX | 买入A~B | 问题
用法：
python3 stale_detector.py
"""
import json
import sys
import os
from datetime import datetime, timezone
DECISIONS_PATH = "/home/hmo/web-dashboard/data/decisions.json"
PORTFOLIO_PATH = "/home/hmo/web-dashboard/data/portfolio.json"
def fetch_prices(codes):
import urllib.request
if not codes:
return {}
symbols, code_map = [], {}
for c in codes:
c = str(c).strip()
p = "sh" if (len(c) == 6 and c[0] in "569") else "sz" if len(c) == 6 else "hk"
sym = f"{p}{c}"
symbols.append(sym)
code_map[sym] = c
try:
req = urllib.request.Request(
f"http://qt.gtimg.cn/q={','.join(symbols)}",
headers={"User-Agent": "curl/7.81"},
)
with urllib.request.urlopen(req, timeout=10) as r:
text = r.read().decode("gbk")
except Exception as e:
print(f"FETCH_FAIL: {e}", file=sys.stderr)
return {}
results = {}
for line in text.strip().split("\n"):
if "=" not in line:
continue
try:
raw = line.split("=", 1)[1].strip().strip('"').strip(";")
fld = raw.split("~")
if len(fld) < 6:
continue
sym = line.split("=", 1)[0].strip().lstrip("v_")
oc = code_map.get(sym)
if not oc:
continue
p = float(fld[3]) if fld[3] else 0
c = fld[32] if len(fld) > 32 else "0"
results[oc] = (p, c)
except (ValueError, IndexError):
continue
return results
def main():
decisions_list = json.load(open(DECISIONS_PATH))
if not isinstance(decisions_list, list):
decisions_list = decisions_list.get("decisions", []) if isinstance(decisions_list, dict) else []
# 只保留有买入区的条目，排除已关闭的（inactive/closed）
EXCLUDED_STATUSES = ("closed", "inactive")
to_check = [d for d in decisions_list if (d.get("entry_low") is not None or d.get("entry_high") is not None) and d.get("status") not in EXCLUDED_STATUSES]
if not to_check:
print("[SILENT] 无需要检查的策略")
return 0
# ----- 组合级监测：读取总仓位 + 弱势比例 -----
position_pct = 0
cash = 0
total_assets = 0
try:
with open(PORTFOLIO_PATH) as f:
pf = json.load(f)
position_pct = pf.get("position_pct", 0)
cash = pf.get("cash", 0)
total_assets = pf.get("total_assets", 0)
except Exception:
pass
# 统计持仓策略中弱势/深套的比例
weak_count = 0
holding_count = 0
for d in decisions_list:
if d.get("type") == "持仓策略" and d.get("status") not in ("closed", "inactive"):
holding_count += 1
cat = d.get("stock_category", "")
if cat in ("弱势", "深套"):
weak_count += 1
weak_ratio = (weak_count / holding_count * 100) if holding_count > 0 else 0
prices = fetch_prices([d["code"] for d in to_check])
now = datetime.now(timezone.utc).astimezone()
found = 0
for d in to_check:
code = d["code"]
name = d.get("name", code)
el = d.get("entry_low")
eh = d.get("entry_high")
sl = d.get("stop_loss")
tp = d.get("take_profit")
ts = d.get("created_at") or d.get("timestamp") or d.get("updated_at", "")
is_wl = "自选" in (d.get("type", ""))
pi = prices.get(code)
if not pi:
continue
price, chg = pi
if price <= 0:
continue
issues, flags = [], []
tag = "[自选]" if is_wl else "[持仓]"
# -- 偏离 --
if is_wl and el and eh:
# 读取 timing_signal 判断策略有效性（timing_signal 字段优先，fallback to action）
current_str = d.get("current", "") or ""
timing_signal = d.get("timing_signal", "") or current_str
has_nonbuy_signal = any(kw in timing_signal for kw in [
"等企稳再入", "等企稳", "弱势持有", "观望",
"不建议买入", "谨慎买入",
])
# 直接计算 R/R（不依赖文本匹配）
rr_invalid = False
if sl and sl > 0 and tp and tp > 0 and price > sl:
rr = (tp - price) / (price - sl)
if rr < 1.5:
rr_invalid = True
# 也检查 tp 是否接近或低于成本（微盈/浮亏止盈）
cost = d.get("cost", 0)
if cost and cost > 0 and tp <= cost * 1.05:
rr_invalid = True
strategy_deficient = has_nonbuy_signal or rr_invalid
# 对自选无止盈位的也标记（策略不完整）
if not tp or tp == 0:
strategy_deficient = True
if el <= price <= eh:
flags.append("[WL_IN]")
if strategy_deficient:
flags.append("[STRATEGY_STALE]")
prefix = "⚠️仓位挤占 " if position_pct > 80 else ""
issues.append(f"[STRATEGY_STALE] {prefix}价{price:.2f}在买入区{el}~{eh}但策略不完整（{'RR='+f'{rr:.2f}<1.5' if rr_invalid else '无止盈位' if not tp else '非买入信号'}），买入区需重评")
else:
prefix = "⚠️仓位挤占 " if position_pct > 80 else ""
issues.append(f"[PUSH] {prefix}价{price:.2f}入买入区{el}~{eh}")
elif price > eh * 1.35:
flags.append("[WL_HIGH]")
issues.append(f"价{price:.2f}高出买入区+{((price/eh)-1)*100:.0f}%，买入区需重评")
elif price > eh * 1.20:
flags.append("[WL_DRIFT]")
issues.append(f"价{price:.2f}高于买入区+{((price/eh)-1)*100:.0f}%")
elif not is_wl and eh:
dp = (price / eh - 1) * 100
if dp > 35:
flags.append("[SEVERE]")
issues.append(f"偏离买入区上沿+{dp:.0f}%")
elif dp > 20:
flags.append("[DRIFT]")
issues.append(f"偏离买入区上沿+{dp:.0f}%")
elif dp > 10:
flags.append("[WARN]")
issues.append(f"偏离买入区上沿+{dp:.0f}%")
# 持仓在买入区内但 R/R 不达标
if el and sl and sl > 0 and tp and tp > 0 and price > sl:
if el <= price <= eh:
rr = (tp - price) / (price - sl)
if rr < 1.5:
flags.append("[RR_WARN]")
issues.append(f"买入区内RR仅{rr:.2f}<1.5，策略需重评")
# -- 距止损/止盈（仅持仓） --
if not is_wl:
if sl and sl > 0:
dsl = (price / sl - 1) * 100
if dsl < 5:
flags.append("[NEAR_SL]")
issues.append(f"距止损仅{dsl:.1f}%")
if tp and tp > 0:
dtp = (tp / price - 1) * 100
if dtp < 5:
# 成本基准校验：止盈标记只有在盈利≥5%时才有效
cost_check = True
cost = d.get("cost")
if cost and cost > 0 and price < cost * 1.05:
cost_check = False
if cost_check:
flags.append("[NEAR_TP]")
issues.append(f"距止盈仅{dtp:.1f}%")
# -- 过期 --
stale_limit = 30 if is_wl else 14
if ts:
try:
ud = datetime.fromisoformat(ts)
if ud.tzinfo is None:
ud = ud.replace(tzinfo=timezone.utc)
days = (now - ud).days
if days > stale_limit:
flags.append("[STALE]")
issues.append(f"{days}天未更新(>{stale_limit})")
except (ValueError, TypeError):
pass
if issues:
print(f"{' '.join(flags)} {tag} {name}({code}) 价{price:.2f}{chg} | 买入{el}~{eh} | {'; '.join(issues)}")
found += 1
if found == 0:
print("[SILENT] 所有策略正常")
# ----- 组合级警报 -----
portfolio_alerts = 0
if holding_count > 0:
if weak_ratio > 40:
print(f"\n[PORTFOLIO_WEAK] 组合弱势比例{weak_ratio:.0f}% ({weak_count}/{holding_count})！仓位{position_pct:.1f}% → 建议系统性减仓")
portfolio_alerts += 1
elif weak_ratio > 30:
print(f"\n[PORTFOLIO_WEAK_MILD] 组合弱势比例{weak_ratio:.0f}% ({weak_count}/{holding_count})，仓位{position_pct:.1f}%，关注")
portfolio_alerts += 1
if position_pct > 80 and holding_count > 0:
# 仓位过满提醒
print(f"[PORTFOLIO_FULL] 总仓位{position_pct:.1f}% > 80%，现金{cash:.0f}({cash/total_assets*100:.1f}%)")
portfolio_alerts += 1
if portfolio_alerts > 0:
found += portfolio_alerts
return found
if __name__ == "__main__":
main()