483 lines
23 KiB
Python
483 lines
23 KiB
Python
#!/usr/bin/env python3
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"""
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per_stock_reassess.py — 按个股触发重评
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对每只传进来的 code 执行 reassess_with_context()，然后写入
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DB holding_strategies 表（纯DB模式，已移除JSON依赖）。
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"""
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import sys, json, os, re
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sys.path.insert(0, "/home/hmo/web-dashboard")
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sys.path.insert(0, "/home/hmo/MoFin")
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from strategy_lifecycle import reassess_with_context as reassess_strategy
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from mo_data import read_decisions, read_portfolio
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def _build_full_analysis(code, entry, result):
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"""从重评结果构建完整九维分析文本"""
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if not result:
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return ""
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lines = []
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name = entry.get("name", code)
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price = result.get("price") or entry.get("price", 0)
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tech = result.get("tech_snapshot") or entry.get("tech_snapshot", "")
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sector = result.get("sector_context") or entry.get("sector_context", "")
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signal = result.get("timing_signal") or entry.get("timing_signal", "")
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category = result.get("stock_category") or entry.get("stock_category", "")
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el = result.get("entry_low") or entry.get("entry_low", 0)
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eh = result.get("entry_high") or entry.get("entry_high", 0)
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sl = result.get("stop_loss") or entry.get("stop_loss", 0)
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tp = result.get("take_profit") or entry.get("take_profit", 0)
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rr = result.get("rr_ratio") or entry.get("rr_ratio", 0)
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act = result.get("action", "")
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# 从tech_snapshot提取关键数据
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ma5 = ma10 = ma20 = ma60 = "?"
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import re
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ma_match = re.search(r'MA5=([\d.]+).*?MA10=([\d.]+).*?MA20=([\d.]+).*?MA60=([\d.]+)', tech)
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if ma_match:
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ma5, ma10, ma20, ma60 = ma_match.groups()
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lines.append(f"【{name}({code}) 九维全析】")
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lines.append("")
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lines.append(f"① 大盘×技术面：价格{price}，MA5={ma5} MA10={ma10} MA20={ma20} MA60={ma60}")
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if el and eh:
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lines.append(f"② 大盘×买入区：当前价{'在买入区' if el <= price <= eh else ('低于买入区' if price < el else '高于买入区')}{el}~{eh}")
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lines.append(f"③ 大盘×资金流：信号={signal}，分类={category}")
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if sector:
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lines.append(f"④ 行业×基本面：{sector}")
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if tech:
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# 提取形态和量价
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shape_m = re.search(r'形态:([^\s]+)', tech)
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vol_m = re.search(r'量价:([^\s]+)', tech)
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shape = shape_m.group(1) if shape_m else "?"
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vol = vol_m.group(1) if vol_m else "?"
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lines.append(f"⑤ 个股×技术面：{shape} | {vol}")
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sr_m = re.search(r'强撑:([\d.]+).*?弱撑:([\d.]+).*?弱压:([\d.]+).*?强压:([\d.]+)', tech)
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if sr_m:
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lines.append(f"⑥ 个股×支撑阻力：强撑{sr_m.group(1)}→弱撑{sr_m.group(2)}→弱压{sr_m.group(3)}→强压{sr_m.group(4)}")
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if sl and tp:
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lines.append(f"⑦ 个股×风报比：止损{sl} 止盈{tp} RR={rr:.1f}")
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if act:
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lines.append(f"⑧ 策略判定：{act[:100]}")
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lines.append(f"⑨ 综合结论：{signal}，建议{'关注买入' if '买入' in signal else '持有观望' if signal == '持有' else '观望等待'}")
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return "\n".join(lines)
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def main():
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codes = [a for a in sys.argv[1:] if not a.startswith("-")]
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if not codes:
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print("[FULL] 无指定编码，跑全量 regenerate_all()")
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from strategy_lifecycle import regenerate_all
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regenerate_all(stdout=False)
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print("[FULL] 全量重评完成")
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return
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# 读现有 decisions
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raw = read_decisions()
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decisions_map = {d["code"]: d for d in raw.get("decisions", []) if d.get("code")}
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ok = 0
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errors = 0
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skipped = 0
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for code in codes:
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entry = decisions_map.get(code)
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if not entry:
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# 不在 decisions 中的自选股 → 从 DB watchlist_stocks 构建entry
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import sqlite3
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_db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
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_db.row_factory = sqlite3.Row
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_wl = _db.execute("SELECT * FROM watchlist_stocks WHERE code=? AND is_active=1", (code,)).fetchone()
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_db.close()
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if _wl:
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entry = {
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"code": code,
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"name": _wl["name"],
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"price": _wl["price"] or 0,
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"cost": 0,
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"shares": 0,
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"entry_low": _wl["entry_low"] or 0,
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"entry_high": _wl["entry_high"] or 0,
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"stop_loss": _wl["stop_loss"] or 0,
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"take_profit": 0,
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"action": "",
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"type": "自选策略",
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"is_watchlist": True,
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"analysis": json.loads(_wl["analysis_json"]) if _wl["analysis_json"] else {}
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}
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print(f"[WL] {code} {_wl['name']}: 从自选表构建entry")
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if not entry:
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print(f"[SKIP] {code}: 不在 decisions 或 watchlist_stocks 中")
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errors += 1
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continue
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try:
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# Always fetch live price for accurate reassessment
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price = 0
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try:
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# 价格从 DB 读取（price_monitor 每2分钟更新，唯一价格入口）
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code_raw = entry.get("code", "")
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price = 0
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import sqlite3
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db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
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db.row_factory = sqlite3.Row
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row = db.execute("SELECT price FROM holdings WHERE code=? AND is_active=1", (code_raw,)).fetchone()
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if not row:
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row = db.execute("SELECT price FROM watchlist_stocks WHERE code=? AND is_active=1", (code_raw,)).fetchone()
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if not row:
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row = db.execute("SELECT price FROM holding_strategies WHERE code=? AND status='active' ORDER BY updated_at DESC LIMIT 1", (code_raw,)).fetchone()
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if row:
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price = row['price'] or 0
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db.close()
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if price > 0:
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print(f" 实时价: {price} (来自DB)")
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else:
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# fallback to DB portfolio data
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_pf_data = read_portfolio()
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for _h in _pf_data.get("holdings", []):
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if _h["code"] == code_raw:
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price = float(_h.get("price", 0))
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break
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if price <= 0:
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price = entry.get("current_price") or entry.get("price") or 0
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except Exception as e:
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print(f" 价格获取失败: {e}", file=sys.stderr)
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price = entry.get("current_price") or entry.get("price") or 0
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# Price diff debounce: skip reassessment if price changed < 1% since last update
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last_price = entry.get("last_reassessed_price") or 0
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if last_price > 0 and price > 0:
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diff_pct = abs(price - last_price) / last_price * 100
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if diff_pct < 1.0:
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print(f" 价差仅{diff_pct:.2f}% (<1%)，跳过重评（上次价={last_price}，现价={price}）")
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skipped += 1
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continue
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# 打印参数调试
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print(f" DEBUG: code={code} name={entry.get('name','')} price={price} cost={entry.get('cost')} shares={entry.get('shares')} action={entry.get('action','')[:30]} is_wl={entry.get('type','') in ('自选策略','watchlist')}", flush=True)
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result = reassess_strategy(
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code=code,
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name=entry.get("name", ""),
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price=price or 0,
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cost=entry.get("cost") or 0,
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shares=entry.get("shares") or 0,
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current_action=entry.get("action", ""),
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is_watchlist=entry.get("type", "") in ("自选策略", "watchlist"),
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)
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if result and result.get("action"):
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# 持仓股止损不下移（移动止损规则）：已有仓位的止损只上不下
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is_held = (entry.get("cost") or 0) > 0 and (entry.get("shares") or 0) > 0 and \
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entry.get("type", "") not in ("自选策略", "watchlist")
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old_stop = entry.get("stop_loss") or 0
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new_stop = result.get("stop_loss") or 0
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if is_held and old_stop > 0 and new_stop > 0 and new_stop < old_stop:
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print(f" 移动止损保护: {new_stop}→保持{old_stop} (持仓止损不下移)")
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result["stop_loss"] = old_stop
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# 同时更新 action 字符串中的止损值
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act = result.get("action", "")
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if act:
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act = re.sub(r'止损[\d.]+', f'止损{old_stop}', act)
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result["action"] = act
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# ── 写入 DB holding_strategies 表（替代 decisions.json）──
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try:
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from mofin_db import get_conn, write_holding_strategy
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_conn = get_conn()
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_db_entry = {
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"code": code,
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"name": entry.get("name", ""),
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"price": price,
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"cost": entry.get("cost", 0),
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"shares": entry.get("shares", 0),
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"stop_loss": result.get("stop_loss", entry.get("stop_loss")),
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"take_profit": result.get("take_profit", entry.get("take_profit")),
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"entry_low": result.get("entry_low", entry.get("entry_low")),
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"entry_high": result.get("entry_high", entry.get("entry_high")),
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"currency": "HKD" if (len(str(code)) == 5 and str(code)[0] in '01') else "CNY",
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"strategy_type": "自选策略" if entry.get("type", "") in ("自选策略", "watchlist") else "持仓策略",
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"action": result.get("action", ""),
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"timing_signal": result.get("timing_signal", entry.get("timing_signal", "")),
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"rr_ratio": result.get("rr_ratio", entry.get("rr_ratio", 0)),
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"tech_snapshot": result.get("tech_snapshot", entry.get("tech_snapshot", "")),
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"stock_category": result.get("stock_category", entry.get("stock_category", "")),
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"sector_context": result.get("sector_context", entry.get("sector_context", "")),
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"status": result.get("status", "active"),
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"source": entry.get("source", "auto"),
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"reason": result.get("action_note", ""),
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"version": entry.get("version", 1),
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"full_analysis": _build_full_analysis(code, entry, result) if result else "",
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}
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write_holding_strategy(_conn, code, entry.get("name", ""), _db_entry)
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_conn.commit()
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_conn.close()
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# 验证写入
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_fa_check = _db_entry.get("full_analysis", "")
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print(f" DEBUG: full_analysis长度={len(_fa_check)} 内容=[{_fa_check[:100]}]")
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# 直接用SQL写入full_analysis
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try:
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_fa_conn = __import__('sqlite3').connect("/home/hmo/MoFin/data/mofin.db")
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_fa_conn.execute("UPDATE holding_strategies SET full_analysis=? WHERE code=? AND status='active'", (_fa_check, code))
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_fa_conn.commit()
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_fa_conn.close()
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print(f" ✅ full_analysis直接SQL写入成功")
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except Exception as _fa_e:
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print(f" ⚠️ 直接SQL写入失败: {_fa_e}")
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_v = __import__('sqlite3').connect(str(__import__('pathlib').Path("/home/hmo/MoFin/data/mofin.db")))
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_fa = _v.execute("SELECT full_analysis FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
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if _fa and _fa[0]: print(f" ✅ full_analysis已写入({len(_fa[0])}字)")
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else: print(f" ⚠️ full_analysis为空")
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_v.close()
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# 用代码构建完整九维分析
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_full_analysis_text = _build_full_analysis(code, entry, result)
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# 保存到DB
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_fa_conn = __import__('sqlite3').connect("/home/hmo/MoFin/data/mofin.db")
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_fa_conn.execute("UPDATE holding_strategies SET full_analysis=? WHERE code=? AND status='active'", (_full_analysis_text, code))
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_fa_conn.commit()
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_fa_conn.close()
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print(f" ✅ 完整九维分析已保存({len(_full_analysis_text)}字)")
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print(f" [DB] holding_strategies 已更新: {code}")
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except Exception as _dbe:
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print(f" [DB FAIL] holding_strategies 写入失败: {_dbe}", file=sys.stderr)
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# 更新 decisions_map 中对应的条目
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updated = entry.copy()
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# 币种标记：HK股保留HKD原始值，A股为CNY
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is_hk = len(str(code)) == 5 and str(code)[0] in '01'
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updated.update({
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"action": result["action"],
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"stop_loss": result.get("stop_loss", entry.get("stop_loss")),
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"entry_low": result.get("entry_low", entry.get("entry_low")),
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"entry_high": result.get("entry_high", entry.get("entry_high")),
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"take_profit": result.get("take_profit"),
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"tech_snapshot": result.get("tech_snapshot", entry.get("tech_snapshot")),
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"timing_signal": result.get("timing_signal", entry.get("timing_signal")),
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"rr_ratio": result.get("rr_ratio", entry.get("rr_ratio", 0)),
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"status": result.get("status", "updated"),
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"price": price,
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"currency": "HKD" if is_hk else "CNY",
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})
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# Save last reassessed price for debounce tracking
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updated["last_reassessed_price"] = price
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decisions_map[code] = updated
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# ——— 初始化多分支策略树 ———
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try:
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sys.path.insert(0, '/home/hmo/MoFin')
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from strategy_tree import init_default_branches
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branches = init_default_branches(
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code,
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entry.get('name', ''),
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result.get('entry_low', 0),
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result.get('entry_high', 0),
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result.get('stop_loss', 0),
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result.get('take_profit', 0),
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)
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st = updated.setdefault('strategy_tree', {})
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st['branches'] = branches
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except Exception:
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pass
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print(f"[OK] {code} {entry.get('name','')}: {result['action'][:80]}")
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ok += 1
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else:
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print(f"[SYNCED] {code}: 无变更")
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ok += 1
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except Exception as e:
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print(f"[ERROR] {code}: {e}", file=sys.stderr)
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import traceback
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traceback.print_exc(file=sys.stderr)
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errors += 1
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# 同步自选股更新回 watchlist_stocks 表（持仓策略已通过 write_holding_strategy 写入 DB）
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try:
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from datetime import datetime as _dt
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import sqlite3
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_db2 = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
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for _code in codes:
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_entry = decisions_map.get(_code)
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if _entry and _entry.get("is_watchlist"):
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_db2.execute("""
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UPDATE watchlist_stocks
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SET entry_low=?, entry_high=?, stop_loss=?, price=?,
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analysis_json=json(?)
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WHERE code=? AND is_active=1
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""", (
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_entry.get("entry_low", 0),
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_entry.get("entry_high", 0),
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_entry.get("stop_loss", 0),
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_entry.get("price", 0),
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json.dumps({
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"action": _entry.get("action",""),
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"take_profit": _entry.get("take_profit", 0),
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"stop_loss": _entry.get("stop_loss", 0),
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"tech_snapshot": _entry.get("tech_snapshot", ""),
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"rr": _entry.get("rr_ratio", 0),
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"reassessed_at": _dt.now().strftime("%Y-%m-%d")
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}, ensure_ascii=False),
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_code
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))
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_db2.commit()
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_db2.close()
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if any(e.get("is_watchlist") for e in [decisions_map.get(c) for c in codes] if e):
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print("[SYNC] 自选股策略已同步回 watchlist_stocks 表")
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except Exception as e:
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print(f"[SYNC FAIL] watchlist_stocks 同步失败: {e}", file=sys.stderr)
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print(f"[DONE] {ok}成功 {skipped}跳过 {errors}失败")
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# ── 第二步：扫描自选股（watchlist），价格偏离买入区>20%触发重评 ──
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scan_watchlist_stocks()
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# ════════════════════════════════════════════════════════════════════
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# 自选股扫描
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# ════════════════════════════════════════════════════════════════════
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def scan_watchlist_stocks():
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"""扫描自选股表 (watchlist_stocks)，对价格偏离买入区 >20% 的股票自动重评。
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偏离公式: max(|price - entry_low|, |price - entry_high|) / entry_low * 100 > 20
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通过 technical_analysis.full_analysis() 获取最新支撑/阻力位，
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更新 entry_low / entry_high / stop_loss / price / analysis_json。
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每轮最多处理 3 只，超过时标记剩余数量待下次扫描。
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"""
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import sqlite3, json
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from datetime import datetime
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from technical_analysis import full_analysis
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from mo_models import is_hk_stock
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DB = '/home/hmo/web-dashboard/data/mofin.db'
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db = sqlite3.connect(DB)
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db.row_factory = sqlite3.Row
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rows = db.execute(
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"SELECT * FROM watchlist_stocks WHERE is_active=1"
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).fetchall()
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if not rows:
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print("[WL-SCAN] 自选股表为空，跳过")
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db.close()
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return
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# ── 筛选偏离 >20% 的股票 ──
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candidates = [] # (code, name, price, entry_low, entry_high, stop_loss, deviation, analysis_json)
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for r in rows:
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code = r["code"]
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name = r["name"]
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price = r["price"] or 0
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entry_low = r["entry_low"] or 0
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entry_high = r["entry_high"] or 0
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stop_loss = r["stop_loss"] or 0
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analysis_json = r["analysis_json"]
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if entry_low <= 0 or price <= 0:
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continue
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dev_low = abs(price - entry_low)
|
||
dev_high = abs(price - entry_high)
|
||
deviation = max(dev_low, dev_high) / entry_low * 100
|
||
|
||
if deviation > 20:
|
||
candidates.append((code, name, price, entry_low, entry_high, stop_loss, deviation, analysis_json))
|
||
|
||
total_needed = len(candidates)
|
||
print(f"[WL-SCAN] 自选股共{len(rows)}只，偏离>20%需重评: {total_needed}只")
|
||
|
||
MAX_PER_RUN = 3
|
||
to_process = candidates[:MAX_PER_RUN]
|
||
remaining = max(0, total_needed - MAX_PER_RUN)
|
||
|
||
if remaining > 0:
|
||
print(f"[WL-SCAN] 本轮限{MAX_PER_RUN}只，剩余{remaining}只待下次扫描")
|
||
|
||
if not to_process:
|
||
print("[WL-SCAN] 无需重评")
|
||
db.close()
|
||
return
|
||
|
||
ok = 0
|
||
errors = 0
|
||
for code, name, price, old_low, old_high, old_stop, deviation, old_analysis_json in to_process:
|
||
print(f"[WL-REASSESS] {code} {name}: 偏离{deviation:.1f}%，触发重评")
|
||
try:
|
||
ta = full_analysis(code)
|
||
if not ta or "error" in ta:
|
||
print(f" [WARN] TA失败: {ta}")
|
||
errors += 1
|
||
continue
|
||
|
||
sr = ta.get("support_resistance", {})
|
||
if "error" in sr:
|
||
print(f" [WARN] 支撑/阻力计算失败: {sr}")
|
||
errors += 1
|
||
continue
|
||
|
||
new_price = ta.get("quote", {}).get("price", price)
|
||
new_entry_low = round(sr.get("weak_support", old_low), 2)
|
||
new_entry_high = round(sr.get("weak_resist", old_high), 2)
|
||
new_stop_loss = round(sr.get("strong_support", old_stop), 2)
|
||
new_take_profit = round(sr.get("strong_resist", 0), 2)
|
||
|
||
# ── 更新 analysis_json + changelog ──
|
||
old_analysis = json.loads(old_analysis_json) if old_analysis_json else {}
|
||
changelog = old_analysis.get("changelog", [])
|
||
changelog.append({
|
||
"action": "auto_reassess_watchlist",
|
||
"reason": f"价格偏离买入区{deviation:.1f}%",
|
||
"old_entry_low": old_low,
|
||
"old_entry_high": old_high,
|
||
"new_entry_low": new_entry_low,
|
||
"new_entry_high": new_entry_high,
|
||
"old_stop_loss": old_stop,
|
||
"new_stop_loss": new_stop_loss,
|
||
"take_profit": new_take_profit,
|
||
"price": new_price,
|
||
"deviation_pct": round(deviation, 1),
|
||
"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M"),
|
||
})
|
||
|
||
new_analysis = {
|
||
**old_analysis,
|
||
"take_profit": new_take_profit,
|
||
"tech_snapshot": {
|
||
"support_resistance": sr,
|
||
"candlestick": ta.get("candlestick", {}),
|
||
"volume": ta.get("volume", {}),
|
||
"analyzed_at": ta.get("analyzed_at", ""),
|
||
},
|
||
"reassessed_at": datetime.now().strftime("%Y-%m-%d"),
|
||
"changelog": changelog,
|
||
}
|
||
|
||
currency = "HKD" if is_hk_stock(code) else "CNY"
|
||
|
||
db.execute("""
|
||
UPDATE watchlist_stocks
|
||
SET entry_low=?, entry_high=?, stop_loss=?, price=?,
|
||
currency=?, analysis_json=?
|
||
WHERE code=? AND is_active=1
|
||
""", (
|
||
new_entry_low, new_entry_high, new_stop_loss,
|
||
new_price, currency, json.dumps(new_analysis, ensure_ascii=False),
|
||
code,
|
||
))
|
||
db.commit()
|
||
print(f" [OK] {code} {name}: 买入区{old_low}-{old_high} -> {new_entry_low}-{new_entry_high}, "
|
||
f"止损{new_stop_loss}, 止盈{new_take_profit}")
|
||
ok += 1
|
||
except Exception as e:
|
||
import traceback
|
||
print(f" [ERROR] {code}: {e}", file=sys.stderr)
|
||
traceback.print_exc(file=sys.stderr)
|
||
errors += 1
|
||
|
||
db.close()
|
||
remaining_msg = f" (剩余{remaining}只)" if remaining else ""
|
||
print(f"[WL-SCAN] DONE: {ok}成功 {errors}失败{remaining_msg}")
|
||
|
||
|
||
if __name__ == "__main__":
|
||
main()
|