知微
729 lines
25 KiB
Python
729 lines
25 KiB
Python
#!/usr/bin/env python3
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"""
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stale_push_wlin.py — 按5步逻辑推送自选股买入区提醒 + 自动触发重评
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5步逻辑：
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1. 筛选 is_watchlist=true 且价在买入区
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2. RR<1.5/无止盈位/非买入signal → 标记 STRATEGY_STALE → 触发自动重评
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3. 可推的：计算每手买入金额和现金占比
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4. 发现 STRATEGY_STALE → 后台跑 per_stock_reassess.py 自动重评
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no_agent模式：有推送→输出；无→静默
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搭配 cron: no_agent=True, 交易日每30分跑一次
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"""
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import subprocess
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import sys
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import re
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import json
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import os
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import threading
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import time
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from datetime import datetime
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try:
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from urllib.request import Request, urlopen
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except ImportError:
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from urllib2 import Request, urlopen
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XMPP_BRIDGE = "http://127.0.0.1:5805/"
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XMPP_USER = "hmo@yoin.fun"
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STALENESS_REPORT = "/home/hmo/web-dashboard/data/strategy_staleness_report.json"
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DETECTOR = "/home/hmo/.hermes/profiles/position-analyst/scripts/stale_detector.py"
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PORTFOLIO_PATH = "/home/hmo/web-dashboard/data/portfolio.json"
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REGEN_SCRIPT = "/home/hmo/.hermes/profiles/position-analyst/scripts/per_stock_reassess.py"
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REGEN_LOCK = "/tmp/.stale_push_wlin_regen.lock"
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MACRO_CTX = "/home/hmo/web-dashboard/data/macro_context.json"
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MARKET_JSON = "/home/hmo/web-dashboard/data/market.json"
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COOLDOWN_PATH = "/home/hmo/web-dashboard/data/push_cooldown.json"
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NON_BUY_SIGNALS = ["观望", "弱势持有", "深套持有"]
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def load_macro_line():
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"""加载大盘和市场的简要描述"""
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parts = []
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try:
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with open(MACRO_CTX) as f:
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m = json.load(f).get("structure", {})
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overall = m.get("overall", "neutral")
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desc = m.get("description", "")
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if "bearish" in overall:
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parts.append("大盘偏弱")
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elif overall == "bullish":
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parts.append("大盘偏强")
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elif desc:
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parts.append(f"大盘{desc}")
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except Exception:
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pass
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try:
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with open(MARKET_JSON) as f:
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mk = json.load(f)
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mood = mk.get("mood", "")
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if mood:
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parts.append(f"市场{mood}")
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except Exception:
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pass
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return " | ".join(parts) if parts else ""
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def is_actionable(cur, timing_signal=""):
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"""检查信号是否可操作。空文本/含非买入关键词 → 不可操作"""
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if not cur and not timing_signal:
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return False # 空文本默认不安全
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for kw in NON_BUY_SIGNALS:
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if cur and kw.lower() in cur.lower():
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return False
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if timing_signal and kw.lower() in timing_signal.lower():
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return False
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return True
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def trigger_regen_sync(stock_codes=None):
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"""同步执行指定个股的重评（等重评完再发报告）"""
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if not stock_codes:
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return
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try:
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cmd = ["python3", REGEN_SCRIPT] + stock_codes
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subprocess.run(cmd, capture_output=True, text=True, timeout=60)
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except subprocess.TimeoutExpired:
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print("[REGEN] 重评超时（60s）", file=sys.stderr)
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except Exception as e:
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print(f"[REGEN] 重评失败: {e}", file=sys.stderr)
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def load_cash():
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"""从 portfolio.json 实时读现金，不硬编码"""
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try:
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with open(PORTFOLIO_PATH) as f:
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data = json.load(f)
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if isinstance(data, dict):
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return data.get("cash", 0)
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if isinstance(data, list) and len(data) > 1 and isinstance(data[1], dict):
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return data[1].get("cash", 0)
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return 0
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except Exception:
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return 0
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_HK_LOT_CACHE = {}
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def hk_lot_size(code):
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"""从腾讯行情API获取港股实际每手股数（字段[60]），带缓存"""
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if code in _HK_LOT_CACHE:
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return _HK_LOT_CACHE[code]
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try:
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url = f"http://qt.gtimg.cn/q=hk{code}"
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req = Request(url, headers={"User-Agent": "curl/7.81"})
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with urlopen(req, timeout=5) as r:
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text = r.read().decode("gbk")
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raw = text.split("=", 1)[1].strip().strip('"').strip(";")
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fld = raw.split("~")
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lot = int(fld[60]) if len(fld) > 60 and fld[60] else 1000
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_HK_LOT_CACHE[code] = lot
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return lot
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except Exception:
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_HK_LOT_CACHE[code] = 1000
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return 1000
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def lot_cost(code, price):
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if str(code).startswith("688"):
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return 200 * price
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elif len(str(code)) == 5:
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lot = hk_lot_size(code)
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try:
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sys.path.insert(0, '/home/hmo/MoFin')
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from hk_rate import hkd_to_cny
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rate = hkd_to_cny()
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except Exception:
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rate = 0.87
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return int(lot * price * rate)
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else:
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return 100 * price
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def push_to_xmpp(text):
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"""通过知微 HTTP bridge 推送到老爸私信"""
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if not text.strip():
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return
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try:
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payload = json.dumps({
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"to": XMPP_USER,
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"body": text.strip(),
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"type": "chat",
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}).encode("utf-8")
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req = Request(XMPP_BRIDGE, data=payload, headers={"Content-Type": "application/json"})
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urlopen(req, timeout=5)
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except Exception as e:
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print(f"[XMPP推送失败] {e}", file=sys.stderr)
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def load_cooldown():
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try:
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with open(COOLDOWN_PATH) as f:
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return json.load(f)
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except Exception:
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return {}
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def save_cooldown(cd):
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try:
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with open(COOLDOWN_PATH, "w") as f:
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json.dump(cd, f, indent=2)
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except Exception:
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pass
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def in_cooldown(code, action_type, cooldown_dict, minutes=30):
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key = f"{code}_{action_type}"
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last = cooldown_dict.get(key, 0)
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elapsed = time.time() - last
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return elapsed < minutes * 60, elapsed, key
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def main():
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r = subprocess.run(
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["python3", DETECTOR], capture_output=True, text=True, timeout=60
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)
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if r.returncode != 0 and r.stderr:
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print(f"[stderr] {r.stderr.strip()}", file=sys.stderr)
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wl_lines = [
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l for l in r.stdout.split("\n")
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if "[WL_IN]" in l and "[自选]" in l
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]
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if not wl_lines:
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return 0
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# 读 stale report
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try:
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with open(STALENESS_REPORT) as f:
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report = json.load(f)
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except Exception:
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report = {"flagged": []}
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code_cur = {i["code"]: i.get("current", "") for i in report.get("flagged", [])}
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# 加载冷却状态
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cooldown = load_cooldown()
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now_ts = time.time()
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# 读 decisions.json 获取完整策略数据
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code_data = {}
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try:
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with open("/home/hmo/web-dashboard/data/decisions.json") as f:
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dec = json.load(f)
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for e in dec.get("decisions", []):
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code_data[e["code"]] = e
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except Exception:
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pass
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cash = load_cash()
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stocks = []
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stale_list = []
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for l in wl_lines:
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m = re.match(r'\[WL_IN\](?:\s+\[\w+\])*\s+\[自选\]\s+(\S+)\((\d+)\)', l)
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if not m:
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continue
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name, code = m.group(1), m.group(2)
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pm = re.search(r'价(\d+\.\d{2})', l)
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if not pm:
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continue
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price = float(pm.group(1))
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zm = re.search(r'买入([\d.]+)~([\d.]+)', l)
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if not zm:
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continue
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buy_low, buy_high = float(zm.group(1)), float(zm.group(2))
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is_stale = "[STRATEGY_STALE]" in l
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cur = code_cur.get(code, "")
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if not is_actionable(cur, code_data.get(code, {}).get("timing_signal", "")) or is_stale:
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stale_list.append((name, code, price, buy_low, buy_high, cur))
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continue
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lot = lot_cost(code, price)
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ratio = lot / cash if cash > 0 else 999
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stocks.append((name, code, price, buy_low, buy_high, lot, ratio))
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if not stocks and not stale_list:
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return 0
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now = datetime.now().strftime("%H:%M")
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lines = []
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# 市场背景
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macro_line = load_macro_line()
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if macro_line:
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lines.append(f"【市场背景】{macro_line}")
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# [重评] 内部流程 — 不在报告中展示，只执行重评
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if stale_list:
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stale_codes = [s[1] for s in stale_list]
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trigger_regen_sync(stale_codes)
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# 重评完成，re-read decisions.json
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code_data = {}
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try:
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with open("/home/hmo/web-dashboard/data/decisions.json") as f:
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dec = json.load(f)
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for e in dec.get("decisions", []):
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code_data[e["code"]] = e
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except Exception:
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pass
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stocks.sort(key=lambda s: (
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0 if len(str(s[1])) == 6 else 1,
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-code_data.get(s[1], {}).get("rr_ratio", 0)
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))
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# 只展示有清晰操作信号的个股：不含"等企稳""关注""信号不充分""neutral"及纯持有信号
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SKIP_KEYWORDS = ["等企稳", "关注", "信号不充分"]
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BUY_KEYWORDS = ["买入", "加仓"]
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actionable = []
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for s in stocks:
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sig = code_data.get(s[1], {}).get("timing_signal", "")
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if not sig:
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continue
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# 跳过非操作信号
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if any(kw in sig for kw in SKIP_KEYWORDS):
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continue
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# 中性信号跳过
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stripped = sig.strip().lower()
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if not stripped or stripped in ("", "neutral", "持有", "深套持有", "弱势持有"):
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continue
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actionable.append(s)
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if not actionable:
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return 0 # 无操作信号 → 静默，不推
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# 加载基本面缓存（PE等）
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fund_cache = {}
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try:
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with open("/home/hmo/web-dashboard/data/multi_tf_cache.json") as f:
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mtf = json.load(f)
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for code, v in mtf.items():
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fund_cache[code] = v.get("fundamentals", {})
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except Exception:
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pass
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# 仓位计算：从holding.xls导入的portfolio.json读取总资产和现金
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n = len(actionable)
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total_assets = 0
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available_cash = 0
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try:
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with open("/home/hmo/web-dashboard/data/portfolio.json") as f:
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pf = json.load(f)
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available_cash = pf.get("cash", 0) or 0
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for h in pf.get("holdings", []):
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mv = h.get("shares", 0) * h.get("price", 0)
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if h.get("currency") == "HKD":
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mv *= h.get("exchange_rate", 0.866)
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total_assets += mv
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total_assets += available_cash
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except Exception:
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total_assets = available_cash * 5 # fallback
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# 加载策略树模块（获取当前情景+分支评估）
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st = None
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scenario_id = ""
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scenario_label = ""
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try:
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import importlib.util
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spec = importlib.util.spec_from_file_location("st_module", "/home/hmo/MoFin/strategy_tree.py")
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st = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(st)
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sc = st.detect_scenario()
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scenario_id = sc.get("id", "")
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scenario_label = sc.get("label", "")
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except Exception:
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pass
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def calc_position(lot_cost, rr, market_factor, cat, code=""):
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# 理论推荐仓位(% of 总资产) — 仅基于RR+市场+品种，不受现金限制
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if rr >= 5:
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theo_pct = 25
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elif rr >= 3:
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theo_pct = 18
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elif rr >= 2:
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theo_pct = 12
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else:
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theo_pct = 8
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if "偏弱" in market_factor:
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theo_pct = int(theo_pct * 0.8)
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elif "偏强" in market_factor:
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theo_pct = int(theo_pct * 1.15)
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if cat in ("蓝筹", "白马"):
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theo_pct = int(theo_pct * 1.2)
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elif cat in ("题材", "短线"):
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theo_pct = int(theo_pct * 0.6)
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elif cat in ("高波动", "成长"):
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theo_pct = int(theo_pct * 0.85)
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theo_pct = max(5, min(30, theo_pct))
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# 当前建议仓位：理论占总资产% → 按现金锁死
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ideal_budget = total_assets * theo_pct / 100
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# 可操作N只时，现金分配不超过 available_cash / n * 1.5
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max_use_cash = (available_cash / max(n, 1)) * 1.5
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budget = min(ideal_budget, max_use_cash, available_cash)
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lots = int(budget / lot_cost) if lot_cost > 0 else 0
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if lots == 0 and lot_cost > 0 and budget > lot_cost * 0.8:
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# 预算覆盖超过80%的1手金额 → 至少1手（仅差一档）
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lots = 1
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lot_cost_total = lots * lot_cost
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if lots == 0:
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pct_actual = 0
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elif total_assets > 0:
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pct_actual = round(lot_cost_total / total_assets * 100)
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else:
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pct_actual = 0
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if lots == 0:
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details = f"预算不足1手（{budget:,.0f}/{lot_cost:,.0f}元）"
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else:
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if len(str(code)) == 5:
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hk_lot = hk_lot_size(code)
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shares = lots * hk_lot
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elif code.startswith("688"):
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shares = lots * 200
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else:
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shares = lots * 100
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details = f"{lots}手（{shares}股，{lot_cost_total:,.0f}元）"
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return theo_pct, pct_actual, details, lots, lot_cost_total
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# ── 换仓评估 ──────────────────────────────────────────────────────
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def score_future_outlook(code_in, h_data, cd_in):
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"""基于决策系统已有的分析数据，评估持仓的未来前景评分。
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评分越低（负数越大）= 前景越差，越值得考虑卖出。
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评分越高（正数越大）= 前景越好，应该保留。
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考虑维度（按重要度排序）：
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1. timing_signal — 决策系统输出的主信号
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2. 技术形态 — bearish/bullish/neutral
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3. 量价关系 — 买卖盘主导
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4. 行业背景 — 板块强弱
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5. 盈亏比RR — 预期收益/风险
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6. 股票类别 — 蓝筹/深套/题材
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"""
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d = cd_in.get(code_in, {})
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if not d:
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return -999 # 无数据=前景未知，保守视为差
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score = 0
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reasons = []
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# 1. timing_signal — 最直接的信号
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signal = (d.get('timing_signal') or '').strip()
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if '买入' in signal or '加仓' in signal:
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score += 3
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reasons.append('有买入信号')
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elif '深套持有' in signal or '弱势持有' in signal:
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score -= 2
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reasons.append('深套/弱势持有')
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elif signal in ('持有', '') or not signal:
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score -= 0.5 # 中性偏弱（没有积极信号就是消极信号）
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reasons.append('无积极信号')
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# 2. 技术形态
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tech = (d.get('tech_snapshot') or '') or ''
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if '/bearish' in tech:
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score -= 1.5
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reasons.append('技术偏空')
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elif '/bullish' in tech:
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score += 1.5
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reasons.append('技术偏多')
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# 3. 量价关系
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if '主动卖盘占优' in tech:
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score -= 1
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reasons.append('卖盘主导')
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elif '主动买盘占优' in tech:
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score += 1
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reasons.append('买盘主导')
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# 4. 行业背景（大跌/大涨）
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||
sector = (d.get('sector_context') or '') or ''
|
||
if '大跌' in sector or '偏弱' in sector:
|
||
score -= 0.5
|
||
if '大涨' in sector or '偏强' in sector:
|
||
score += 0.5
|
||
|
||
# 5. 盈亏比RR
|
||
rr = d.get('rr_ratio', 0) or 0
|
||
if rr >= 2:
|
||
score += 1
|
||
reasons.append(f'RR{rr:.1f}≥2')
|
||
elif rr < 1:
|
||
score -= 0.5
|
||
reasons.append(f'RR{rr:.1f}<1')
|
||
|
||
# 6. 股票类别
|
||
cat = (d.get('stock_category') or '') or ''
|
||
if '蓝筹' in cat or '白马' in cat:
|
||
score += 0.5
|
||
elif '深套' in cat or '弱势' in cat:
|
||
score -= 0.5
|
||
|
||
return round(score, 1)
|
||
|
||
def evaluate_swap(lot_cost_target, rr, sig, tp, sl, name, code, price_in,
|
||
total_assets_in, cash_in, pf_in, cd_in):
|
||
"""现金不足时评估是否卖差票换推荐股。
|
||
|
||
核心逻辑：
|
||
- 已发生的亏损是沉没成本，不参与决策
|
||
- 用"全面分析"法评估每个持仓的未来前景（基于决策系统既有数据）
|
||
- 优先卖前景最差的票，保留前景好的票（无论当前盈亏%）
|
||
- 对目标票(RR>=3+买入信号)才有换仓资格
|
||
|
||
返回（推荐文案str, 缺口float）或 (None, gap)
|
||
"""
|
||
gap = lot_cost_target - cash_in
|
||
# 目标票质量门槛
|
||
if rr < 3.0 or gap <= 0 or gap > total_assets_in * 0.5:
|
||
return None, gap
|
||
if not any(kw in sig for kw in ["买入", "加仓", "建仓"]):
|
||
return None, gap
|
||
|
||
# 收集持仓数据 + 前景评分
|
||
ph = []
|
||
for h in pf_in.get("holdings", []):
|
||
hs = h.get("shares", 0) or 0
|
||
hp = h.get("price", 0) or 0
|
||
hc = h.get("cost", 0) or 0
|
||
if hs <= 0 or hp <= 0:
|
||
continue
|
||
hmv = hs * hp
|
||
h_code = str(h.get("code", ""))
|
||
if len(h_code) <= 5:
|
||
hmv *= 0.866 # approximate HKD→CNY
|
||
hpl_pct = (hp - hc) / hc * 100 if hc else 0
|
||
|
||
# 全面评分（越低越差，越建议卖）
|
||
fscore = score_future_outlook(h_code, h, cd_in)
|
||
|
||
ph.append({
|
||
"code": h_code,
|
||
"name": h.get("name", ""),
|
||
"shares": hs,
|
||
"price": hp,
|
||
"cost": hc,
|
||
"mv": round(hmv),
|
||
"pl_pct": round(hpl_pct, 1),
|
||
"score": fscore,
|
||
})
|
||
|
||
# 按前景评分升序（最差的排最前面）
|
||
ph.sort(key=lambda x: x["score"])
|
||
|
||
# 打印调试信息：所有持仓的前景评分
|
||
# print(f"[SWAP_DEBUG] 前景评分(越低越差):", file=sys.stderr)
|
||
# for x in ph[:10]:
|
||
# print(f" {x['name']}({x['code']}) 评分{x['score']} 亏{x['pl_pct']}% 市值{x['mv']:,}", file=sys.stderr)
|
||
|
||
# 只考虑评分<=0（前景差或中性偏弱）的作为减仓候选
|
||
candidates = [h for h in ph if h["score"] <= 0]
|
||
if not candidates:
|
||
return None, gap
|
||
|
||
# 贪心选评分最差的，凑够现金缺口（最多2只）
|
||
selected = []
|
||
cash_freed = 0
|
||
for h in candidates:
|
||
if cash_freed >= gap:
|
||
break
|
||
cash_freed += h["mv"]
|
||
selected.append(h)
|
||
|
||
if cash_freed < gap or len(selected) > 2:
|
||
return None, gap
|
||
|
||
# 计算目标票的预期涨幅
|
||
if tp and tp > 0:
|
||
target_gain_pct = (tp - price_in) / price_in * 100
|
||
else:
|
||
target_gain_pct = rr * 3
|
||
|
||
# 构建推荐文案
|
||
sell_parts = []
|
||
sell_names = []
|
||
for h in selected:
|
||
# 每个被选股票配一句"为什么卖它"
|
||
reason = f"前景评分{h['score']}"
|
||
if h['pl_pct'] <= -30:
|
||
reason += "深套"
|
||
elif h['pl_pct'] <= -15:
|
||
reason += f"亏损{h['pl_pct']}%"
|
||
sell_parts.append(f"{h['name']}({h['code']}) {h['shares']}股 亏{h['pl_pct']}% ({reason})")
|
||
sell_names.append(h['name'])
|
||
sell_desc = "；".join(sell_parts)
|
||
|
||
new_budget = cash_in + cash_freed
|
||
new_lots = int(new_budget / lot_cost_target) if lot_cost_target > 0 else 0
|
||
if new_lots == 0:
|
||
return None, gap
|
||
if code.startswith("688"):
|
||
new_shares = new_lots * 200
|
||
elif len(code) <= 5:
|
||
new_shares = new_lots * hk_lot_size(code)
|
||
else:
|
||
new_shares = new_lots * 100
|
||
new_cost = new_lots * lot_cost_target
|
||
new_pct = round(new_cost / total_assets_in * 100) if total_assets_in > 0 else 0
|
||
|
||
text = (
|
||
f"换仓建议：卖{sell_desc}"
|
||
f"→腾{round(cash_freed):,}元"
|
||
f"→买{name}({code}) {new_lots}手({new_shares}股,{round(new_cost):,}元)"
|
||
f"占{new_pct}%仓位"
|
||
f"（止损{sl}(-{round((price_in-sl)/price_in*100,1)}%)"
|
||
f"止盈{tp}(+{round(target_gain_pct,1)}%)"
|
||
f" RR={rr}）\n"
|
||
f" 理由：{', '.join(sell_names)}前景评分最低，"
|
||
f"继续持有无积极信号且技术偏弱；"
|
||
f"换到有明确信号和止损的标的，预期收益更优。"
|
||
)
|
||
return text, gap
|
||
|
||
# 标准格式：每个可操作标的 — 大盘/行业/个股三面 + 仓位
|
||
lines.append(f"【💡 操作建议】（当前{n}只自选可操作 | 总资产{total_assets:,.0f}元 现金{available_cash:,.0f}元）")
|
||
for s in actionable:
|
||
name, code, price, buy_low, buy_high, lot, ratio = s
|
||
d = code_data.get(code, {})
|
||
sl = d.get("stop_loss", 0)
|
||
tp = d.get("take_profit", 0)
|
||
rr = d.get("rr_ratio", 0)
|
||
sig = d.get("timing_signal", "")
|
||
sector = d.get("sector_context", "")
|
||
tech = d.get("tech_snapshot", "")
|
||
note = d.get("note", "")
|
||
d_factors = d.get("signal_factors", [])
|
||
cat = d.get("stock_category", "")
|
||
|
||
# 提取技术位
|
||
ss = {"强撑":"-", "弱撑":"-", "弱压":"-", "强压":"-"}
|
||
for tag in ss:
|
||
m = re.search(rf'{tag}:([\d.]+)', tech)
|
||
if m:
|
||
ss[tag] = m.group(1)
|
||
|
||
# 基本面
|
||
fund = fund_cache.get(code, {})
|
||
pe = fund.get("pe", 0)
|
||
eps = fund.get("eps", 0)
|
||
pe_str = f"PE{pe:.0f}" if pe else ""
|
||
eps_str = f"EPS{eps:.2f}" if eps else ""
|
||
|
||
# 从 signal_factors 提取各维度
|
||
def _match_factor(prefix):
|
||
for f in d_factors:
|
||
if f.startswith(prefix):
|
||
return f
|
||
return ""
|
||
|
||
market_factor = _match_factor("大盘")
|
||
sector_factor = _match_factor("行业")
|
||
value_factor = _match_factor("高估值") or _match_factor("低估值") or _match_factor("蓝筹") or pe_str or ""
|
||
news_factor = _match_factor("消息")
|
||
tech_factor = _match_factor("净利") or _match_factor("组合") or ""
|
||
|
||
# 构建分析行
|
||
parts = []
|
||
if market_factor:
|
||
parts.append(f"大盘{market_factor.replace('大盘','')}")
|
||
if sector_factor:
|
||
parts.append(f"行业{sector_factor.replace('行业','')}")
|
||
if pe_str or value_factor:
|
||
parts.append(value_factor or pe_str)
|
||
if news_factor:
|
||
parts.append(news_factor)
|
||
if not parts:
|
||
parts.append(sector or cat or "")
|
||
|
||
analysis = " | ".join(p for p in parts if p)
|
||
|
||
# 仓位计算
|
||
theo_pct, actual_pct, details, lots, lot_cost_total = calc_position(
|
||
lot, rr, market_factor, cat, code
|
||
)
|
||
|
||
pfx = "" if len(code) == 6 else "HK$"
|
||
|
||
# 取分支动作类型
|
||
branch_action = "hold"
|
||
branch_rationale = ""
|
||
if st and scenario_id:
|
||
try:
|
||
results = st.evaluate_branches(code, scenario_id, price, d.get("shares", 0), d.get("cost", 0))
|
||
applicable = [r for r in results if r.get("applicable")]
|
||
if applicable:
|
||
best = min(applicable, key=lambda r: r.get("priority", 999))
|
||
branch_action = best.get("action_type", "hold")
|
||
branch_rationale = best.get("rationale", "")
|
||
except Exception:
|
||
pass
|
||
|
||
# 冷却检查：相同股+相同操作30分钟内不发
|
||
cooled, elapsed, cd_key = in_cooldown(code, branch_action, cooldown)
|
||
if cooled:
|
||
continue
|
||
|
||
action_tag = "⚠️" if lots == 0 else "🛒"
|
||
|
||
# 换仓评估：现金不足时评估是否卖差票换推荐股
|
||
swap_text = None
|
||
if lots == 0:
|
||
swap_text, _ = evaluate_swap(
|
||
lot, rr, sig, tp, sl, name, code, price,
|
||
total_assets, available_cash, pf, code_data
|
||
)
|
||
|
||
lines.append(
|
||
f" {action_tag} {name}({code}) {pfx}{price:.2f} 买区{buy_low}~{buy_high} | "
|
||
f"1手{lot:,.0f}元 RR={rr:.1f} 损{sl} 盈{tp}\n"
|
||
f" {analysis}\n"
|
||
f" 技术{ss['强撑']}→{ss['弱撑']}→{ss['弱压']}→{ss['强压']} | 信号{sig}\n"
|
||
f" 仓位：理论{theo_pct}%×总资产 | 建议{actual_pct}%（{details}）"
|
||
)
|
||
|
||
if swap_text:
|
||
lines[-1] += f"\n {swap_text}"
|
||
|
||
# 分支描述
|
||
branch_line = ""
|
||
if branch_action != "hold":
|
||
branch_line = f" 【{scenario_label}→{branch_action}】{branch_rationale}"
|
||
if branch_line:
|
||
lines[-1] += f"\n{branch_line}"
|
||
|
||
# 记录推送时间（冷却计时用）
|
||
cooldown[cd_key] = now_ts
|
||
|
||
save_cooldown(cooldown)
|
||
|
||
# 修正可操作数量（剔除冷却跳过后的实际数量）
|
||
actual_n = len(lines) - (1 if macro_line else 0) - 1 # 减去市场背景 + 操作建议标题
|
||
if actual_n != n:
|
||
# 更新操作建议行
|
||
for i, ln in enumerate(lines):
|
||
if "【💡 操作建议】" in ln:
|
||
lines[i] = f"【💡 操作建议】（当前{actual_n}只自选可操作 | 总资产{total_assets:,.0f}元 现金{available_cash:,.0f}元）"
|
||
break
|
||
|
||
if actual_n <= 0:
|
||
return 0 # 全部冷却中 → 静默，不推
|
||
|
||
lines.insert(0, f"【知微】自选买入提醒 {now} | 总资产{total_assets:,.0f}元")
|
||
out = "\n".join(lines)
|
||
print(out)
|
||
push_to_xmpp(out)
|
||
return 0
|
||
|
||
|
||
if __name__ == "__main__":
|
||
sys.exit(main())
|