cleanup: remove stale scripts/ copies (authoritative in deploy/profile-scripts/)

This commit is contained in:
hmo
2026-07-28 08:47:39 +08:00
parent c572bbc3ef
commit 835314fbb0
2 changed files with 0 additions and 751 deletions
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#!/usr/bin/env python3
"""candidate_filter.py — 候选股多级过滤管道
从 candidates 表读取未过滤的候选,逐级执行过滤:
Stage 2: 多日K线确认(量价连续性)
Stage 3: 技术位分析(MA位置)
Stage 4: 资金性质(大单流向)
Stage 5: 基本面(PE/PB/行业)
用法: python3 candidate_filter.py [--stage 2|3|4|5] [--code XXXXXX]
"""
import sys, json, urllib.request, sqlite3, re, time
from pathlib import Path
from datetime import datetime
DB_PATH = Path("/home/hmo/MoFin/data/mofin.db")
UA = "Mozilla/5.0"
def get_conn():
c = sqlite3.connect(str(DB_PATH), timeout=30)
c.execute("PRAGMA busy_timeout=30000")
return c
def log_candidate(conn, code, stage, passed, detail):
"""记录过滤日志"""
conn.execute(
"UPDATE candidates SET log = COALESCE(log, '[]')"
)
# SQLite JSON操作
existing = conn.execute("SELECT log FROM candidates WHERE code=?", (code,)).fetchone()
if existing and existing[0]:
try:
logs = json.loads(existing[0])
except:
logs = []
else:
logs = []
logs.append({"stage": stage, "passed": passed, "detail": detail, "time": datetime.now().strftime("%m-%d %H:%M")})
conn.execute("UPDATE candidates SET log=? WHERE code=?", (json.dumps(logs, ensure_ascii=False), code))
# ── Stage 2: 多日K线确认 ──
def fetch_daily_klines(code):
"""拉取近10日日K线(Sina 240分钟线=日K"""
raw = str(code).strip()
if raw.startswith(("6", "9")):
prefix = "sh"
elif raw.startswith(("0", "3")):
prefix = "sz"
else:
return None
import subprocess as _sp, json as _json
url = f"http://money.finance.sina.com.cn/quotes_service/api/json_v2.php/CN_MarketData.getKLineData?symbol={prefix}{raw}&scale=240&ma=5&datalen=10"
try:
r = _sp.run(["curl", "-s", "--noproxy", "*", url], capture_output=True, timeout=10)
data = _json.loads(r.stdout)
if not data:
return None
result = []
for k in data:
result.append({
"date": k.get("day", "")[:10],
"open": float(k["open"]),
"close": float(k["close"]),
"high": float(k["high"]),
"low": float(k["low"]),
"volume": int(k["volume"]),
"price": float(k["close"]),
"change_pct": 0,
})
# 计算涨跌幅
for i in range(1, len(result)):
prev = result[i-1]["close"]
if prev > 0:
result[i]["change_pct"] = (result[i]["close"] / prev - 1) * 100
return result
except Exception as e:
return None
return None
def stage2_confirm(code, name, klines):
"""第二关:多日K线确认
检查:多日量价配合、建仓特征
"""
if not klines or len(klines) < 3:
return False, 0, "K线不足3日"
recent = klines[-5:] # 最近5日
score = 0
checks = []
# 1. 成交量连续递增
vols = [k["volume"] for k in recent]
vol_rising = sum(1 for i in range(len(vols)-1) if vols[i] < vols[i+1])
if vol_rising >= 3:
score += 2
checks.append(f"量增{vol_rising}/4日")
elif vol_rising >= 2:
score += 1
checks.append(f"量微增{vol_rising}/4日")
# 2. 涨放量、跌缩量
up_vol = sum(k["volume"] for k in recent if k["change_pct"] >= 0)
down_vol = sum(k["volume"] for k in recent if k["change_pct"] < 0)
if down_vol > 0 and up_vol / down_vol > 1.5:
score += 2
checks.append(f"涨量/跌量={up_vol/down_vol:.1f}")
elif down_vol > 0 and up_vol / down_vol > 1:
score += 1
# 3. 价格趋势
closes = [k["close"] for k in recent]
up_days = sum(1 for i in range(1, len(closes)) if closes[i] > closes[i-1])
if up_days >= 3:
score += 2
checks.append(f"{up_days}/4日")
elif up_days >= 2:
score += 1
# 4. 无异常放量(单日>3倍均量=可能出货)
avg_vol = sum(vols) / len(vols) if vols else 1
max_ratio = max(v / avg_vol for v in vols) if avg_vol > 0 else 1
if max_ratio < 2.5:
score += 1
else:
checks.append(f"异常量{max_ratio:.0f}")
passed = score >= 4
detail = f"评分{score}/7 | {'; '.join(checks)}"
return passed, score, detail
# ── Stage 3: 技术位分析 ──
def stage3_technical(code, name, klines):
"""第三关:技术位(当日数据估算)"""
if not klines or len(klines) == 0:
return False, 0, "无数据"
today = klines[-1]
price = today.get("price", 0)
high = today.get("high", 0)
low = today.get("low", 0)
score = 0
checks = []
if price <= 0:
return False, 0, "价格无效"
# 日内位置(在高低点中下段还有空间)
if high > low:
pos = (price - low) / (high - low)
if pos < 0.7:
score += 1
checks.append(f"日内位置{pos:.0%}")
# 有明确支撑(今日低点作为参考支撑)
if low > 0 and price > low:
score += 1
checks.append(f"支撑{low:.2f}")
# 有上涨空间(今日高点作为参考阻力)
if high > price:
upside = (high / price - 1) * 100
if upside > 2:
score += 1
checks.append(f"空间{upside:.0f}%")
passed = score >= 2
return passed, score, "; ".join(checks) if checks else "基础通过"
# ── Stage 4: 资金性质分析 ──
def stage4_capital_flow(code, name):
"""第四关:资金性质(从腾讯实时行情提取外盘/内盘比)"""
raw = str(code).strip()
if raw.startswith(("6", "9")):
prefix = "sh"
elif raw.startswith(("0", "3")):
prefix = "sz"
else:
return False, 0, "非A股"
import subprocess as _sp
url = f"http://qt.gtimg.cn/q={prefix}{raw}"
try:
r = _sp.run(["curl", "-s", url], capture_output=True, timeout=10)
text = r.stdout.decode("gbk", errors="ignore")
parts = text.split("~")
if len(parts) < 40:
return False, 0, "数据不足"
# 腾讯字段:[7]=外盘(主动买,股),[8]=内盘(主动卖,股)
try:
outer = int(float(parts[7])) if parts[7] else 0 # 外盘
inner = int(float(parts[8])) if parts[8] else 0 # 内盘
except:
return False, 0, "解析失败"
if outer <= 0 or inner <= 0:
return False, 0, "无盘口数据"
score = 0
ratio = outer / inner if inner > 0 else 1
checks = []
if ratio > 1.3:
score += 2
checks.append(f"外/内={ratio:.2f}")
elif ratio > 1.0:
score += 1
checks.append(f"买稍强{ratio:.2f}")
else:
checks.append(f"卖稍强{ratio:.2f}")
# 绝对量也说明资金活跃度
total = outer + inner
if total > 50000000: # >5000万股
score += 1
checks.append(f"活跃{total/10000:.0f}")
return score >= 1, score, "; ".join(checks)
except:
return False, 0, "接口失败"
# ── Stage 5: 基本面 ──
def stage5_fundamental(code, name, price):
"""第五关:基本面
从已有数据判断,不调外部API
"""
conn = get_conn()
score = 0
checks = []
# PE(从stocks表或live_prices
r = conn.execute("SELECT 1 FROM holdings WHERE code=? AND is_active=1", (code,)).fetchone()
is_holding = r is not None
if is_holding:
checks.append("已持仓")
else:
score += 1 # 新标的加分
# 检查是否已被其他候选覆盖
r2 = conn.execute("SELECT code FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
if r2:
checks.append("已有策略")
else:
score += 1
conn.close()
return score >= 1, score, "; ".join(checks) if checks else "新标的"
# ── 主流程 ──
def main():
stage_filter = None
single_code = None
for i, arg in enumerate(sys.argv[1:]):
if arg == "--stage" and i+1 < len(sys.argv):
stage_filter = int(sys.argv[i+2])
if arg == "--code" and i+1 < len(sys.argv):
single_code = sys.argv[i+2]
conn = get_conn()
# 读待过滤的候选
query = "SELECT code, name, reason FROM candidates WHERE 1=1"
params = []
if single_code:
query += " AND code=?"
params.append(single_code)
else:
query += " AND (pass_final IS NULL OR pass_final=0)"
rows = conn.execute(query, params).fetchall()
print(f"[FILTER] 待处理候选: {len(rows)}", flush=True)
stages = [(2, stage2_confirm, "多日K线"), (3, stage3_technical, "技术位"),
(4, stage4_capital_flow, "资金流"), (5, stage5_fundamental, "基本面")]
for code, name, reason in rows:
current_score = 0
print(f" {code} {name}", flush=True)
# 获取K线(多关需要)
klines = None
for stage_num, stage_fn, stage_name in stages:
if stage_filter and stage_num != stage_filter:
continue
# 检查是否已通过此关
col = f"pass_s{stage_num}"
existing = conn.execute(f"SELECT {col} FROM candidates WHERE code=?", (code,)).fetchone()
if existing and existing[0]:
continue
if stage_num in (2, 3) and klines is None:
klines = fetch_daily_klines(code)
if stage_num == 2:
passed, sscore, detail = stage_fn(code, name, klines)
conn.execute("UPDATE candidates SET score_2nd=?, pass_s2=?, reason=? WHERE code=?",
(sscore, 1 if passed else 0, detail, code))
log_candidate(conn, code, 2, passed, detail)
print(f" S2:{'' if passed else ''} {detail}", flush=True)
elif stage_num == 3:
passed, sscore, detail = stage_fn(code, name, klines)
conn.execute("UPDATE candidates SET score_3rd=?, pass_s3=?, reason=? WHERE code=?",
(sscore, 1 if passed else 0, detail, code))
log_candidate(conn, code, 3, passed, detail)
print(f" S3:{'' if passed else ''} {detail}", flush=True)
elif stage_num == 4:
passed, sscore, detail = stage_fn(code, name)
conn.execute("UPDATE candidates SET score_4th=?, pass_s4=?, reason=? WHERE code=?",
(sscore, 1 if passed else 0, detail, code))
log_candidate(conn, code, 4, passed, detail)
print(f" S4:{'' if passed else ''} {detail}", flush=True)
elif stage_num == 5:
price = 0 # 从live_prices获取
r = conn.execute("SELECT price FROM live_prices WHERE code=?", (code,)).fetchone()
if r: price = r[0]
passed, sscore, detail = stage_fn(code, name, price)
conn.execute("UPDATE candidates SET score_5th=?, pass_s5=?, reason=? WHERE code=?",
(sscore, 1 if passed else 0, detail, code))
log_candidate(conn, code, 5, passed, detail)
print(f" S5:{'' if passed else ''} {detail}", flush=True)
# 计算综合评分
s2 = conn.execute("SELECT score_2nd FROM candidates WHERE code=?", (code,)).fetchone()[0] or 0
s3 = conn.execute("SELECT score_3rd FROM candidates WHERE code=?", (code,)).fetchone()[0] or 0
s4 = conn.execute("SELECT score_4th FROM candidates WHERE code=?", (code,)).fetchone()[0] or 0
s5 = conn.execute("SELECT score_5th FROM candidates WHERE code=?", (code,)).fetchone()[0] or 0
final = current_score + s2 + s3 + s4 + s5
conn.execute("UPDATE candidates SET score_final=?, pass_final=1 WHERE code=?",
(final, code))
conn.commit()
conn.close()
print(f"[FILTER] 完成", flush=True)
if __name__ == "__main__":
main()
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#!/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 holding_strategies + 自选策略的DB双源数据。
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
sys.path.insert(0, '/home/hmo/MoFin')
from mo_data import read_portfolio, read_decisions, read_watchlist, get_price, get_prices_batch
def fetch_prices(codes):
"""统一价格源:优先 stock_quote.py,腾讯API降级为兜底"""
if not codes:
return {}
# 尝试用 stock_quote.py 获取(脚本强制规范)
try:
import subprocess
script = None
for p in ["/home/hmo/MoFin/scripts/stock_quote.py", "/home/hmo/MoFin/stock_quote.py"]:
if os.path.exists(p):
script = p
break
if script:
result = subprocess.run(
[sys.executable, script] + [str(c) for c in codes],
capture_output=True, text=True, timeout=30
)
if result.returncode == 0 and result.stdout.strip():
results = {}
for line in result.stdout.strip().split("\n"):
if not line.strip():
continue
try:
item = json.loads(line)
code = str(item.get("code", ""))
price = item.get("price")
change = item.get("change_pct", 0)
if code and price is not None:
results[code] = (float(price), float(change))
except (json.JSONDecodeError, ValueError):
continue
if results:
return results
except Exception as e:
print(f"[STALE] stock_quote.py 回退: {e}", file=sys.stderr)
# 兜底:mo_data.get_prices_batch
try:
raw = get_prices_batch(codes)
if raw:
return {code: (p, chg) for code, (p, chg) in raw.items()}
except Exception as e:
print(f"FETCH_FAIL (fallback): {e}", file=sys.stderr)
return {}
def main():
decisions_list = read_decisions()
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]
# ----- 补充自选(从 holding_strategies 读取,watchlist_stocks 已废弃) -----
try:
import sqlite3
db = sqlite3.connect('/home/hmo/MoFin/data/mofin.db')
db.row_factory = sqlite3.Row
wl_rows = db.execute(
"SELECT code, name, entry_low, entry_high, stop_loss, take_profit, rr_ratio, timing_signal, action "
"FROM holding_strategies WHERE status='active' AND decision_type='自选策略' "
"AND entry_low IS NOT NULL AND entry_high IS NOT NULL"
).fetchall()
db.close()
existing_codes = {d["code"] for d in to_check}
for row in wl_rows:
code = str(row["code"])
if code in existing_codes:
continue
entry_low = row["entry_low"]
entry_high = row["entry_high"]
if not entry_low or not entry_high or entry_low <= 0:
continue
action = row["action"] or ""
timing_signal = row["timing_signal"] or "买入"
wl_entry = {
"code": code,
"name": row["name"] or code,
"entry_low": entry_low,
"entry_high": entry_high,
"stop_loss": row["stop_loss"],
"type": "自选策略",
"action": action,
"timing_signal": timing_signal,
}
to_check.append(wl_entry)
except Exception as e:
print(f"[WATCHLIST_MERGE FAIL] {e}", file=sys.stderr)
if not to_check:
print("[SILENT] 无需要检查的策略")
return 0
# ----- 自选股买入区偏离自动重评 (从 holding_strategies 读,watchlist_stocks 已废弃) -----
try:
import subprocess, sqlite3
db = sqlite3.connect('/home/hmo/MoFin/data/mofin.db')
db.row_factory = sqlite3.Row
wl_stocks = db.execute(
"SELECT code, name, entry_low, entry_high "
"FROM holding_strategies WHERE status='active' AND decision_type='自选策略' "
"AND entry_low IS NOT NULL AND entry_high IS NOT NULL AND entry_low > 0"
).fetchall()
db.close()
reassess_scripts = []
for ws in wl_stocks:
code, name, wl_el, wl_eh = ws
if not wl_el or not wl_el or wl_el <= 0:
continue
center = (wl_el + wl_eh) / 2
# 从 decisions 拿实时价
price_map = fetch_prices([code])
cur_price = price_map.get(code, (None, None))[0]
if not cur_price or cur_price <= 0:
continue
drift = (cur_price / center - 1) * 100
# 触发条件:价格偏离>15% 或 买入区明确错误(价格完全在区间外且偏离>50%)
price_outside = cur_price < wl_el or cur_price > wl_eh
if abs(drift) > 15 or (price_outside and abs(drift) > 50):
reassess_scripts.append(code)
print(f"[AUTO_REASSESS] {name}({code}) 价{cur_price:.2f}偏离买入区中心{center:.2f} {drift:+.0f}% → 触发重评")
if reassess_scripts:
# 调用 per_stock_reassess(每轮最多5只,防LLM慢导致整批超时;其余下轮继续)
reassess_path = None
for p in ['/home/hmo/MoFin/scripts/per_stock_reassess.py',
'/home/hmo/.hermes/profiles/position-analyst/scripts/per_stock_reassess.py']:
if os.path.exists(p):
reassess_path = p
break
if reassess_path:
MAX_PER_RUN = 5
batch = reassess_scripts[:MAX_PER_RUN]
if len(reassess_scripts) > MAX_PER_RUN:
print(f"[AUTO_REASSESS] 本轮限{MAX_PER_RUN}只,剩余{len(reassess_scripts)-MAX_PER_RUN}只下轮继续")
for code in batch:
try:
# LLM 重评冷启动 20-100sdeepseek-v4-pro 更慢 → 480s
r = subprocess.run(['python3', reassess_path, code],
capture_output=True, text=True, timeout=480)
out = r.stdout.strip()[:200] if r.stdout else ""
err = r.stderr.strip()[:200] if r.stderr else ""
print(f"{code}: exited={r.returncode} {out}")
except subprocess.TimeoutExpired:
print(f"{code}: 超时480s(LLM仍慢),下轮重试")
except Exception as e:
print(f"[AUTO_REASSESS FAIL] {e}")
# ----- 结束 自选股重评 -----
# 🔁 重评后重新从DB读取策略数据,刷新to_check
try:
decisions_list = read_decisions()
if not isinstance(decisions_list, list):
decisions_list = decisions_list.get("decisions", []) if isinstance(decisions_list, dict) else []
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]
# 重新合并自选(从 holding_strategies 读)
db2 = sqlite3.connect('/home/hmo/MoFin/data/mofin.db')
db2.row_factory = sqlite3.Row
wl_rows2 = db2.execute(
"SELECT code, name, entry_low, entry_high, stop_loss, take_profit, rr_ratio, timing_signal, action "
"FROM holding_strategies WHERE status='active' AND decision_type='自选策略' "
"AND entry_low IS NOT NULL AND entry_high IS NOT NULL AND entry_low > 0"
).fetchall()
db2.close()
existing_codes2 = {d["code"] for d in to_check}
for row in wl_rows2:
code = str(row["code"])
if code in existing_codes2:
continue
entry_low = row["entry_low"]
entry_high = row["entry_high"]
if not entry_low or not entry_high or entry_low <= 0:
continue
action = row["action"] or ""
timing_signal = row["timing_signal"] or "买入"
wl_entry = {
"code": code,
"name": row["name"] or code,
"entry_low": entry_low,
"entry_high": entry_high,
"stop_loss": row["stop_loss"],
"type": "自选策略",
"action": action,
"timing_signal": timing_signal,
}
to_check.append(wl_entry)
except Exception as e:
print(f"[RELOAD FAIL] {e}", file=sys.stderr)
# ----- 组合级监测:读取总仓位 + 弱势比例 -----
position_pct = 0
cash = 0
total_assets = 0
try:
pf = read_portfolio()
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 not issues and not flags:
# 自选在买入区上沿与20%之间(零标记漏洞):标记为小幅偏离
if el and eh and price > eh:
flags.append("[WL_DRIFT]")
flags.append("[STRATEGY_STALE]")
issues.append(f"[STRATEGY_STALE] 价{price:.2f}超买入区上沿+{((price/eh)-1)*100:.1f}%,买入区需重评")
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]")
issues.append(f"[STRATEGY_STALE] 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:
issues.append(f"[PUSH] 价{price:.2f}入买入区{el}~{eh}")
elif price > eh * 1.35:
flags.append("[WL_HIGH]")
flags.append("[STRATEGY_STALE]")
issues.append(f"[STRATEGY_STALE] 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]")
flags.append("[STRATEGY_STALE]")
issues.append(f"[STRATEGY_STALE] 价{price:.2f}高出买入区+{((price/eh)-1)*100:.0f}%,买入区需重评")
elif price > eh:
flags.append("[WL_DRIFT]")
flags.append("[STRATEGY_STALE]")
issues.append(f"[STRATEGY_STALE] 价{price:.2f}超买入区上沿+{((price/eh)-1)*100:.1f}%,买入区需重评")
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:
# 成本基准校验:浮盈>5%时止损是利润保护,不是危险信号
# (mirrors NEAR_TP cost_check logic at line 195-198)
cost = d.get("cost")
if cost and cost > 0 and price > cost * 1.05:
flags.append("[PROFIT_PROTECT]")
pnl = (price / cost - 1) * 100
issues.append(f"距止损仅{dsl:.1f}%(利润保护,浮盈{pnl:.0f}%)")
else:
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:
# 仅输出有明确操作信号的行:[PUSH]=推荐买入, [STRATEGY_STALE]=需重评
# 静默其他纯信息行(如仅"价XX高出/高于买入区"而无操作建议)
if any("[PUSH]" in i or "[STRATEGY_STALE]" in i for i in 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()