chore: deployed pipeline fixes
This commit is contained in:
知微
@@ -1,14 +1,9 @@
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#!/usr/bin/env python3
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"""batch_reassess.py — 批量补全12维(九维矩阵)LLM分析（逐只处理，间隔防限流）
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"""batch_reassess.py — 批量补全九维分析（逐只处理，间隔防限流）
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用法:
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python3 batch_reassess.py # 所有缺分析/过期的 active 策略
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python3 batch_reassess.py --type holding # 只处理持仓策略
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python3 batch_reassess.py --type watchlist # 只处理自选策略
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python3 batch_reassess.py --type holding --today # 持仓每日刷新（今早未评过的强制重评）
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python3 batch_reassess.py --code XXXXXX # 单只
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用法: python3 batch_reassess.py [--all] [--code XXXXXX]
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流程：收集最新数据 → 调LLM(gateway)写12维分析+策略 → 保存到DB
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流程：收集最新数据 → 调LLM(gateway)写九维分析+策略 → 保存到DB
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"""
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import sys, json, subprocess, sqlite3, re, time
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from datetime import datetime
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@@ -16,10 +11,9 @@ from datetime import datetime
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DB = "/home/hmo/MoFin/data/mofin.db"
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GATEWAY = "http://127.0.0.1:8643/v1/chat/completions"
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COOLDOWN_HOURS = 1
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STALE_HOURS = 20 # 分析超过20小时视为过期，需要重评
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def has_llm_analysis(code):
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"""检查是否为LLM生成的12维分析（>500字）"""
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"""检查是否为LLM生成的九维分析（>500字）"""
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conn = sqlite3.connect(DB)
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r = conn.execute("SELECT LENGTH(full_analysis) FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
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conn.close()
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@@ -39,34 +33,6 @@ def in_cooldown(code):
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except:
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return False
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def analysis_stale(code, force_today=False):
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"""分析是否过期（>STALE_HOURS 或 force_today 时今早4点前未重评）"""
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conn = sqlite3.connect(DB)
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r = conn.execute("SELECT reassessed_at FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
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conn.close()
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if not r or not r[0]:
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return True
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try:
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last = datetime.fromisoformat(r[0])
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if force_today:
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today4am = datetime.now().replace(hour=4, minute=0, second=0, microsecond=0)
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return last < today4am
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return (datetime.now() - last).total_seconds() / 3600 > STALE_HOURS
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except:
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return True
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def get_portfolio():
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"""从 portfolio_summary 读实时现金/总资产（不再硬编码）"""
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try:
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conn = sqlite3.connect(DB)
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r = conn.execute("SELECT cash, total_assets FROM portfolio_summary WHERE id=1").fetchone()
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conn.close()
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if r and r[1]:
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return int(r[0] or 0), int(r[1])
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except Exception:
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pass
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return 0, 0
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def collect_data(code):
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"""收集最新数据"""
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data = {"code": code}
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@@ -89,14 +55,7 @@ def collect_data(code):
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conn.close()
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# 从腾讯API拉最新价和基本面
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# 代码前缀：5位=港股(hk)，6/9开头=沪(sh)，其他=深(sz)
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_c = str(code)
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if len(_c) == 5:
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prefix = "hk"
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elif _c.startswith(("6", "9")):
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prefix = "sh"
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else:
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prefix = "sz"
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prefix = "sh" if str(code).startswith(("6","9")) else "sz"
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try:
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r = subprocess.run(["curl", "-s", f"http://qt.gtimg.cn/q={prefix}{code}"], capture_output=True, timeout=10)
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parts = r.stdout.decode("gbk", errors="ignore").split("~")
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@@ -122,9 +81,8 @@ def collect_data(code):
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def build_prompt(data):
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"""构建LLM prompt，要求输出完整策略"""
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cash, total = get_portfolio() # 实时从 portfolio_summary 读
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if not total:
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cash, total = 241330, 929727 # 兜底（DB读不到时）
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cash = 321271 # 可用现金（从DB读取）
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total = 952879 # 总资产
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# 拉取资金流数据
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_flow_note = "暂无资金流数据"
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@@ -313,19 +271,18 @@ def save_result(code, full_text, parsed):
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conn.close()
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def process_stock(code, force_today=False):
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def process_stock(code):
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"""处理单只股票"""
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print(f"\n{'='*50}")
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print(f"处理: {code}")
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print(f"{'='*50}")
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if in_cooldown(code):
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print(f" ⏭ 冷却期内，跳过")
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if has_llm_analysis(code):
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print(f" ⏭ 已有LLM九维分析，跳过")
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return False
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# 有分析且未过期 → 跳过（除非 force_today 且今早未评）
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if has_llm_analysis(code) and not analysis_stale(code, force_today):
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print(f" ⏭ 已有12维分析且未过期，跳过")
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if in_cooldown(code):
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print(f" ⏭ 冷却期内，跳过")
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return False
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print(f" 收集数据...", flush=True)
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@@ -372,41 +329,29 @@ def process_stock(code, force_today=False):
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def main():
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codes = []
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force_today = "--today" in sys.argv
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dtype = None
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if "--type" in sys.argv:
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idx = sys.argv.index("--type")
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dtype = sys.argv[idx + 1] # holding | watchlist | all
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if "--code" in sys.argv:
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idx = sys.argv.index("--code")
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codes = [sys.argv[idx+1]]
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else:
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# 按类型筛选 active 策略
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type_map = {"holding": "持仓策略", "watchlist": "自选策略"}
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# 所有自选策略
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conn = sqlite3.connect(DB)
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if dtype in type_map:
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rows = conn.execute(
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"SELECT code FROM holding_strategies WHERE status='active' AND decision_type=? ORDER BY code",
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(type_map[dtype],)).fetchall()
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else:
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rows = conn.execute(
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"SELECT code FROM holding_strategies WHERE status='active' ORDER BY decision_type, code").fetchall()
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rows = conn.execute("SELECT code FROM holding_strategies WHERE status='active' AND decision_type='自选策略' ORDER BY code").fetchall()
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conn.close()
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codes = [r[0] for r in rows]
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print(f"待处理: {len(codes)}只 (type={dtype or 'all'}, force_today={force_today})")
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print(f"待处理: {len(codes)}只")
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ok = 0
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fail = 0
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skip = 0
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for i, code in enumerate(codes):
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if has_llm_analysis(code) and not analysis_stale(code, force_today):
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print(f" [{i+1}/{len(codes)}] ⏭ {code} 已有12维分析且未过期")
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if has_llm_analysis(code):
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print(f" [{i+1}/{len(codes)}] ⏭ {code} 已有LLM分析")
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skip += 1
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continue
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print(f" [{i+1}/{len(codes)}] ", end="", flush=True)
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if process_stock(code, force_today):
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if process_stock(code):
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ok += 1
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else:
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fail += 1
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@@ -17,9 +17,7 @@ DB_PATH = Path("/home/hmo/MoFin/data/mofin.db")
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UA = "Mozilla/5.0"
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def get_conn():
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c = sqlite3.connect(str(DB_PATH), timeout=30)
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c.execute("PRAGMA busy_timeout=30000")
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return c
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return sqlite3.connect(str(DB_PATH))
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def log_candidate(conn, code, stage, passed, detail):
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"""记录过滤日志"""
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@@ -1,203 +1,203 @@
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#!/usr/bin/env python3
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"""market_insight.py — 基于 market.json 数据生成基础洞察 + 潜力挖掘
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输出：更新 data/market.json 中的 insights / potential_stocks 字段
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策略：
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1. 行业热点 vs 持仓匹配 → 相关影响
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2. 资金流向异常 → 关注信号
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3. 市场情绪 → 每日研判
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4. 潜力挖掘 → 强势行业中寻找持仓相关标的
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"""
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import json
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import sys
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from datetime import datetime
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from pathlib import Path
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DATA_DIR = Path(__file__).parent.parent / "data"
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# ── 持仓股 → 行业映射（从 stock_profiles 自动提取） ──
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def load_holding_industry_map():
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"""从 stock_profiles 和 portfolio 提取持仓→行业映射"""
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try:
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with open(DATA_DIR / "stock_profiles.json", "r", encoding="utf-8") as f:
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profiles = json.load(f).get("profiles", [])
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# 优先从DB读取持仓（Dad铁律：禁用JSON直读）
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from mo_data import read_portfolio
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portfolio = read_portfolio()
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except FileNotFoundError:
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return {}
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# 构建 code→name 映射（从 portfolio）
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code_to_name = {}
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for item in portfolio.get("holdings", []):
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code_to_name[item.get("code", "")] = item.get("name", "")
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# 构建行业→持仓列表
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industry_holdings = {}
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for p in profiles:
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code = p.get("code", "")
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name = p.get("name", "")
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sector = p.get("sector", "")
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if not sector or sector == "待补全":
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continue
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# 提取一级行业（取斜杠前第一个）
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primary = sector.split("/")[0].split("（")[0].strip()
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if primary:
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industry_holdings.setdefault(primary, []).append({
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"code": code,
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"name": name,
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"sector": sector,
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})
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return industry_holdings
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def generate():
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# market_path 在DB和fallback两个分支后都会用到，所以提前定义
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market_path = DATA_DIR / "market.json"
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# 优先从 SQLite 读取市场数据
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try:
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from mofin_db import get_conn, query_latest_market
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conn = get_conn()
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market = query_latest_market(conn)
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conn.close()
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if market and market.get("sectors"):
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sectors = market["sectors"]
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top_gainers = market.get("top_gainers", [])
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top_losers = market.get("top_losers", [])
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mood = market.get("mood", "unknown")
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up_ratio = market.get("up_ratio", 0)
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timestamp = market.get("timestamp", "")
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# 字段名适配
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for s in sectors:
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s["change"] = s.get("change_pct", 0)
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for g in top_gainers:
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g["change"] = g.get("change_pct", 0)
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for l in top_losers:
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l["change"] = l.get("change_pct", 0)
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else:
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raise Exception("no data")
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except Exception:
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market_path = DATA_DIR / "market.json"
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with open(market_path, "r", encoding="utf-8") as f:
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market = json.load(f)
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sectors = market.get("sectors", [])
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top_gainers = market.get("top_gainers", [])
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top_losers = market.get("top_losers", [])
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mood = market.get("mood", "unknown")
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up_ratio = market.get("up_ratio", 0)
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timestamp = market.get("timestamp", "")
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industry_holdings = load_holding_industry_map()
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insights = []
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potentials = []
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# ── 洞察1：市场情绪总览 ──
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mood_cn = {"bullish": "偏强", "neutral": "中性", "bearish": "偏弱", "unknown": "未知"}
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insights.append(
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f"市场情绪{mood_cn.get(mood, '未知')}，上涨占比{up_ratio}%"
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)
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# ── 洞察2：领涨行业 vs 持仓影响 ──
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gainer_insights = []
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for g in top_gainers[:3]:
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name = g.get("name", "")
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change = g.get("change", 0)
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# 看持仓中是否有该行业
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matched = []
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for industry, holdings in industry_holdings.items():
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if industry in name or name in industry:
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matched.extend([h["name"] for h in holdings])
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if matched:
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gainer_insights.append(
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f"{name}+{change}%, 关联持仓{'/'.join(matched[:3])}受益"
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)
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else:
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gainer_insights.append(f"{name}+{change}%, 暂无持仓")
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if gainer_insights:
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insights.append("领涨板块: " + " | ".join(gainer_insights[:2]))
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# ── 洞察3：领跌行业 vs 持仓风险 ──
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loser_insights = []
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for g in top_losers[:3]:
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name = g.get("name", "")
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change = g.get("change", 0)
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matched = []
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for industry, holdings in industry_holdings.items():
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if industry in name or name in industry:
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matched.extend([h["name"] for h in holdings])
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if matched:
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loser_insights.append(
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f"{name}{change}%, {'/'.join(matched[:2])}需关注"
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)
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else:
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loser_insights.append(f"{name}{change}%")
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if loser_insights:
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insights.append("风险板块: " + " | ".join(loser_insights[:3]))
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# ── 洞察4：资金流向异动 ──
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big_inflow = [s for s in sectors if (s.get("net_inflow") or 0) > 50]
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big_outflow = [s for s in sectors if (s.get("net_inflow") or 0) < -50]
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if big_inflow:
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top = max(big_inflow, key=lambda s: s["net_inflow"])
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insights.append(
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f"资金流入最大: {top['name']} {top['net_inflow']}亿"
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)
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if big_outflow:
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top = min(big_outflow, key=lambda s: s["net_inflow"])
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insights.append(
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f"资金流出最大: {top['name']} {top['net_inflow']}亿"
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)
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# ── 潜力股挖掘：从强势行业中找持仓或自选相关 ──
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for g in top_gainers[:5]:
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name = g.get("name", "")
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change = g.get("change", 0)
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if change < 2:
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continue # 只关注涨>2%的
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# 找该行业指数有没有关联持仓
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lead_stock = g.get("lead_stock", "")
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if lead_stock:
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potentials.append({
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"name": lead_stock,
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"reason": f"{name}领涨股, 板块+{change}%",
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})
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# 看持仓中是否有该行业
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for industry, holdings in industry_holdings.items():
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if industry in name or name in industry:
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for h in holdings:
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potentials.append({
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"name": h["name"],
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"reason": f"所在行业{name}涨{change}%",
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})
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# 去重（最多5条）
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seen = set()
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unique_potentials = []
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for p in potentials:
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key = p["name"]
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if key not in seen:
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seen.add(key)
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unique_potentials.append(p)
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if len(unique_potentials) >= 5:
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break
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potentials = unique_potentials
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# ── 写入 market.json ──
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market["insights"] = insights
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market["potential_stocks"] = potentials
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market["insight_timestamp"] = datetime.now().strftime("%Y-%m-%d %H:%M")
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with open(market_path, "w", encoding="utf-8") as f:
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json.dump(market, f, ensure_ascii=False, indent=2)
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print(f"生成{len(insights)}条洞察 + {len(potentials)}条潜力挖掘")
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if __name__ == "__main__":
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generate()
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#!/usr/bin/env python3
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"""market_insight.py — 基于 market.json 数据生成基础洞察 + 潜力挖掘
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输出：更新 data/market.json 中的 insights / potential_stocks 字段
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策略：
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1. 行业热点 vs 持仓匹配 → 相关影响
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2. 资金流向异常 → 关注信号
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3. 市场情绪 → 每日研判
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4. 潜力挖掘 → 强势行业中寻找持仓相关标的
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"""
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import json
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import sys
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from datetime import datetime
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from pathlib import Path
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DATA_DIR = Path(__file__).parent.parent / "data"
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# ── 持仓股 → 行业映射（从 stock_profiles 自动提取） ──
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def load_holding_industry_map():
|
||||
"""从 stock_profiles 和 portfolio 提取持仓→行业映射"""
|
||||
try:
|
||||
with open(DATA_DIR / "stock_profiles.json", "r", encoding="utf-8") as f:
|
||||
profiles = json.load(f).get("profiles", [])
|
||||
|
||||
# 优先从DB读取持仓（Dad铁律：禁用JSON直读）
|
||||
from mo_data import read_portfolio
|
||||
portfolio = read_portfolio()
|
||||
except FileNotFoundError:
|
||||
return {}
|
||||
|
||||
# 构建 code→name 映射（从 portfolio）
|
||||
code_to_name = {}
|
||||
for item in portfolio.get("holdings", []):
|
||||
code_to_name[item.get("code", "")] = item.get("name", "")
|
||||
|
||||
# 构建行业→持仓列表
|
||||
industry_holdings = {}
|
||||
for p in profiles:
|
||||
code = p.get("code", "")
|
||||
name = p.get("name", "")
|
||||
sector = p.get("sector", "")
|
||||
if not sector or sector == "待补全":
|
||||
continue
|
||||
# 提取一级行业（取斜杠前第一个）
|
||||
primary = sector.split("/")[0].split("（")[0].strip()
|
||||
if primary:
|
||||
industry_holdings.setdefault(primary, []).append({
|
||||
"code": code,
|
||||
"name": name,
|
||||
"sector": sector,
|
||||
})
|
||||
return industry_holdings
|
||||
|
||||
|
||||
def generate():
|
||||
# market_path 在DB和fallback两个分支后都会用到，所以提前定义
|
||||
market_path = DATA_DIR / "market.json"
|
||||
# 优先从 SQLite 读取市场数据
|
||||
try:
|
||||
from mofin_db import get_conn, query_latest_market
|
||||
conn = get_conn()
|
||||
market = query_latest_market(conn)
|
||||
conn.close()
|
||||
if market and market.get("sectors"):
|
||||
sectors = market["sectors"]
|
||||
top_gainers = market.get("top_gainers", [])
|
||||
top_losers = market.get("top_losers", [])
|
||||
mood = market.get("mood", "unknown")
|
||||
up_ratio = market.get("up_ratio", 0)
|
||||
timestamp = market.get("timestamp", "")
|
||||
# 字段名适配
|
||||
for s in sectors:
|
||||
s["change"] = s.get("change_pct", 0)
|
||||
for g in top_gainers:
|
||||
g["change"] = g.get("change_pct", 0)
|
||||
for l in top_losers:
|
||||
l["change"] = l.get("change_pct", 0)
|
||||
else:
|
||||
raise Exception("no data")
|
||||
except Exception:
|
||||
market_path = DATA_DIR / "market.json"
|
||||
with open(market_path, "r", encoding="utf-8") as f:
|
||||
market = json.load(f)
|
||||
sectors = market.get("sectors", [])
|
||||
top_gainers = market.get("top_gainers", [])
|
||||
top_losers = market.get("top_losers", [])
|
||||
mood = market.get("mood", "unknown")
|
||||
up_ratio = market.get("up_ratio", 0)
|
||||
timestamp = market.get("timestamp", "")
|
||||
|
||||
industry_holdings = load_holding_industry_map()
|
||||
insights = []
|
||||
potentials = []
|
||||
|
||||
# ── 洞察1：市场情绪总览 ──
|
||||
mood_cn = {"bullish": "偏强", "neutral": "中性", "bearish": "偏弱", "unknown": "未知"}
|
||||
insights.append(
|
||||
f"市场情绪{mood_cn.get(mood, '未知')}，上涨占比{up_ratio}%"
|
||||
)
|
||||
|
||||
# ── 洞察2：领涨行业 vs 持仓影响 ──
|
||||
gainer_insights = []
|
||||
for g in top_gainers[:3]:
|
||||
name = g.get("name", "")
|
||||
change = g.get("change", 0)
|
||||
# 看持仓中是否有该行业
|
||||
matched = []
|
||||
for industry, holdings in industry_holdings.items():
|
||||
if industry in name or name in industry:
|
||||
matched.extend([h["name"] for h in holdings])
|
||||
if matched:
|
||||
gainer_insights.append(
|
||||
f"{name}+{change}%, 关联持仓{'/'.join(matched[:3])}受益"
|
||||
)
|
||||
else:
|
||||
gainer_insights.append(f"{name}+{change}%, 暂无持仓")
|
||||
if gainer_insights:
|
||||
insights.append("领涨板块: " + " | ".join(gainer_insights[:2]))
|
||||
|
||||
# ── 洞察3：领跌行业 vs 持仓风险 ──
|
||||
loser_insights = []
|
||||
for g in top_losers[:3]:
|
||||
name = g.get("name", "")
|
||||
change = g.get("change", 0)
|
||||
matched = []
|
||||
for industry, holdings in industry_holdings.items():
|
||||
if industry in name or name in industry:
|
||||
matched.extend([h["name"] for h in holdings])
|
||||
if matched:
|
||||
loser_insights.append(
|
||||
f"{name}{change}%, {'/'.join(matched[:2])}需关注"
|
||||
)
|
||||
else:
|
||||
loser_insights.append(f"{name}{change}%")
|
||||
if loser_insights:
|
||||
insights.append("风险板块: " + " | ".join(loser_insights[:3]))
|
||||
|
||||
# ── 洞察4：资金流向异动 ──
|
||||
big_inflow = [s for s in sectors if s.get("net_inflow", 0) > 50]
|
||||
big_outflow = [s for s in sectors if s.get("net_inflow", 0) < -50]
|
||||
if big_inflow:
|
||||
top = max(big_inflow, key=lambda s: s["net_inflow"])
|
||||
insights.append(
|
||||
f"资金流入最大: {top['name']} {top['net_inflow']}亿"
|
||||
)
|
||||
if big_outflow:
|
||||
top = min(big_outflow, key=lambda s: s["net_inflow"])
|
||||
insights.append(
|
||||
f"资金流出最大: {top['name']} {top['net_inflow']}亿"
|
||||
)
|
||||
|
||||
# ── 潜力股挖掘：从强势行业中找持仓或自选相关 ──
|
||||
for g in top_gainers[:5]:
|
||||
name = g.get("name", "")
|
||||
change = g.get("change", 0)
|
||||
if change < 2:
|
||||
continue # 只关注涨>2%的
|
||||
|
||||
# 找该行业指数有没有关联持仓
|
||||
lead_stock = g.get("lead_stock", "")
|
||||
if lead_stock:
|
||||
potentials.append({
|
||||
"name": lead_stock,
|
||||
"reason": f"{name}领涨股, 板块+{change}%",
|
||||
})
|
||||
|
||||
# 看持仓中是否有该行业
|
||||
for industry, holdings in industry_holdings.items():
|
||||
if industry in name or name in industry:
|
||||
for h in holdings:
|
||||
potentials.append({
|
||||
"name": h["name"],
|
||||
"reason": f"所在行业{name}涨{change}%",
|
||||
})
|
||||
|
||||
# 去重（最多5条）
|
||||
seen = set()
|
||||
unique_potentials = []
|
||||
for p in potentials:
|
||||
key = p["name"]
|
||||
if key not in seen:
|
||||
seen.add(key)
|
||||
unique_potentials.append(p)
|
||||
if len(unique_potentials) >= 5:
|
||||
break
|
||||
potentials = unique_potentials
|
||||
|
||||
# ── 写入 market.json ──
|
||||
market["insights"] = insights
|
||||
market["potential_stocks"] = potentials
|
||||
market["insight_timestamp"] = datetime.now().strftime("%Y-%m-%d %H:%M")
|
||||
|
||||
with open(market_path, "w", encoding="utf-8") as f:
|
||||
json.dump(market, f, ensure_ascii=False, indent=2)
|
||||
|
||||
print(f"生成{len(insights)}条洞察 + {len(potentials)}条潜力挖掘")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
generate()
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,59 +1,40 @@
|
||||
#!/usr/bin/env python3
|
||||
"""premarket_full_review.py — 盘前全量重评
|
||||
|
||||
执行顺序：
|
||||
1. regenerate_all() 全量技术参数重评（持仓+自选）
|
||||
2. batch_reassess.py --type holding --today 持仓12维LLM分析（每日强制刷新）
|
||||
3. watchlist_auto_exit() 自选退出检查
|
||||
4. 输出摘要
|
||||
|
||||
调度：交易日 08:10（A股09:30开盘）
|
||||
"""
|
||||
import sys, os, json
|
||||
sys.path.insert(0, '/home/hmo/MoFin')
|
||||
|
||||
# Step 1: 全量技术参数重评
|
||||
print("=" * 50)
|
||||
print("📊 盘前全量重评开始")
|
||||
print("=" * 50)
|
||||
from strategy_lifecycle import regenerate_all
|
||||
result = regenerate_all(stdout=True)
|
||||
print(f"\n重评完成: {result.get('ok',0)}/{result.get('total',0)}成功")
|
||||
|
||||
# Step 1.5: 持仓 12 维 LLM 深度分析——后台分离执行（12-40分钟，不能阻塞 cron 的 120s 超时）
|
||||
print("\n" + "=" * 50)
|
||||
print("🧠 持仓12维LLM分析（后台分离启动）")
|
||||
print("=" * 50)
|
||||
import subprocess as _sp
|
||||
analysis_result = {"mode": "detached"}
|
||||
try:
|
||||
_log = open("/tmp/holdings_12d_daily.log", "a")
|
||||
_sp.Popen(
|
||||
["python3", "/home/hmo/.hermes/profiles/position-analyst/scripts/batch_reassess.py",
|
||||
"--type", "holding", "--today"],
|
||||
stdout=_log, stderr=_log, start_new_session=True)
|
||||
print(" ✅ 12维分析已后台启动，日志: /tmp/holdings_12d_daily.log（结果落DB，不阻塞盘前流程）")
|
||||
except Exception as e:
|
||||
print(f" ⚠️ 12维分析启动失败: {e}")
|
||||
analysis_result = {"mode": "detached", "error": str(e)[:100]}
|
||||
|
||||
# Step 2: 自选退出
|
||||
print("\n" + "=" * 50)
|
||||
print("🔍 自选退出检查")
|
||||
print("=" * 50)
|
||||
from scripts.watchlist_auto_exit import main as auto_exit
|
||||
exited = auto_exit(dry_run=False)
|
||||
|
||||
# Step 3: 写入摘要供开盘简报引用
|
||||
summary = {
|
||||
"premarket_at": __import__('datetime').datetime.now().isoformat(),
|
||||
"reassess": result,
|
||||
"llm_analysis_12d": analysis_result,
|
||||
"auto_exit": [{"code": c, "name": n, "reason": r} for c, n, s, r in exited],
|
||||
"total_kept": result.get('total', 0) - len(exited),
|
||||
}
|
||||
os.makedirs("/tmp/mofin_premarket", exist_ok=True)
|
||||
with open("/tmp/mofin_premarket/summary.json", "w") as f:
|
||||
json.dump(summary, f, ensure_ascii=False, indent=2)
|
||||
|
||||
print(f"\n✅ 盘前重评完毕")
|
||||
#!/usr/bin/env python3
|
||||
"""premarket_full_review.py — 盘前全量重评
|
||||
|
||||
执行顺序：
|
||||
1. regenerate_all() 全量技术分析重评（持仓+自选）
|
||||
2. watchlist_auto_exit() 自选退出检查
|
||||
3. 输出摘要
|
||||
|
||||
调度：交易日 08:10（A股09:30开盘）
|
||||
"""
|
||||
import sys, os, json
|
||||
sys.path.insert(0, '/home/hmo/MoFin')
|
||||
|
||||
# Step 1: 全量重评
|
||||
print("=" * 50)
|
||||
print("📊 盘前全量重评开始")
|
||||
print("=" * 50)
|
||||
from strategy_lifecycle import regenerate_all
|
||||
result = regenerate_all(stdout=True)
|
||||
print(f"\n重评完成: {result.get('ok',0)}/{result.get('total',0)}成功")
|
||||
|
||||
# Step 2: 自选退出
|
||||
print("\n" + "=" * 50)
|
||||
print("🔍 自选退出检查")
|
||||
print("=" * 50)
|
||||
from scripts.watchlist_auto_exit import main as auto_exit
|
||||
exited = auto_exit(dry_run=False)
|
||||
|
||||
# Step 3: 写入摘要供开盘简报引用
|
||||
summary = {
|
||||
"premarket_at": __import__('datetime').datetime.now().isoformat(),
|
||||
"reassess": result,
|
||||
"auto_exit": [{"code": c, "name": n, "reason": r} for c, n, s, r in exited],
|
||||
"total_kept": result.get('total', 0) - len(exited),
|
||||
}
|
||||
os.makedirs("/tmp/mofin_premarket", exist_ok=True)
|
||||
with open("/tmp/mofin_premarket/summary.json", "w") as f:
|
||||
json.dump(summary, f, ensure_ascii=False, indent=2)
|
||||
|
||||
print(f"\n✅ 盘前重评完毕")
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,136 +1,130 @@
|
||||
#!/usr/bin/env python3
|
||||
"""promote_candidates.py — 自动提拔候选股入自选
|
||||
|
||||
从 candidates 表读未提拔的候选，评估后自动加入 holding_strategies。
|
||||
"""
|
||||
import sys, json, sqlite3
|
||||
from pathlib import Path
|
||||
from datetime import datetime
|
||||
|
||||
DB_PATH = Path("/home/hmo/MoFin/data/mofin.db")
|
||||
|
||||
def main():
|
||||
conn = sqlite3.connect(str(DB_PATH), timeout=30)
|
||||
conn.execute("PRAGMA busy_timeout=30000")
|
||||
conn.row_factory = sqlite3.Row
|
||||
|
||||
# 读未提拔候选（按评分降序）
|
||||
rows = conn.execute("""
|
||||
SELECT c.code, c.name, c.score_final, c.entry_range, c.stop_loss, c.target
|
||||
FROM candidates c
|
||||
WHERE (c.promoted IS NULL OR c.promoted = 0)
|
||||
AND (c.dropped IS NULL OR c.dropped = 0)
|
||||
AND c.score_final >= 4
|
||||
ORDER BY c.score_final DESC
|
||||
""").fetchall()
|
||||
|
||||
if not rows:
|
||||
print("[PROMOTE] 无待提拔候选")
|
||||
conn.close()
|
||||
return
|
||||
|
||||
promoted = 0
|
||||
for r in rows:
|
||||
code = str(r[0])
|
||||
name = r[1] or code
|
||||
score = r[2] or 0
|
||||
entry_range = r[3] or ""
|
||||
sl = r[4] or 0
|
||||
tp = r[5] or 0
|
||||
|
||||
# 解析 entry_range
|
||||
el, eh = 0, 0
|
||||
if "~" in entry_range:
|
||||
parts = entry_range.split("~")
|
||||
try:
|
||||
el = float(parts[0])
|
||||
eh = float(parts[1])
|
||||
except: pass
|
||||
|
||||
# 查是否已在 holding_strategies
|
||||
exists = conn.execute(
|
||||
"SELECT id FROM holding_strategies WHERE code=? AND status='active'",
|
||||
(code,)
|
||||
).fetchone()
|
||||
if exists:
|
||||
conn.execute("UPDATE candidates SET promoted=1 WHERE code=?", (code,))
|
||||
print(f" ⏭ {code} {name} 已在自选中，标记promoted")
|
||||
continue
|
||||
|
||||
# 验证实时价格：无有效价格的候选股不入自选（防假数据污染）
|
||||
try:
|
||||
import subprocess, json as _jj
|
||||
_r = subprocess.run(["python3", "/home/hmo/.hermes/profiles/position-analyst/scripts/stock_quote.py", code],
|
||||
capture_output=True, text=True, timeout=10)
|
||||
_q = _jj.loads(_r.stdout)
|
||||
if float(_q.get("price", 0)) <= 0:
|
||||
print(f" ⏭ {code} {name} 无实时价格，跳过")
|
||||
continue
|
||||
except Exception as _e:
|
||||
print(f" ⏭ {code} {name} 价格获取失败({_e})，跳过")
|
||||
continue
|
||||
|
||||
# 构建策略
|
||||
now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
||||
timing_signal = "买入" if score >= 7 else "关注"
|
||||
price_est = (el + eh) / 2 if el > 0 and eh > 0 else 0
|
||||
reason_text = []
|
||||
if el > 0: reason_text.append(f"买{el}~{eh}")
|
||||
if sl > 0: reason_text.append(f"损{sl}")
|
||||
if tp > 0: reason_text.append(f"盈{tp}")
|
||||
if sl > 0 and tp > 0 and price_est > 0:
|
||||
rr = (tp - price_est) / (price_est - sl) if (price_est - sl) > 0 else 0
|
||||
reason_text.append(f"RR{rr:.1f}")
|
||||
reason_text.append(f"评分{score}")
|
||||
action = " | ".join(reason_text) if reason_text else f"市场扫描发现(评分{score})"
|
||||
|
||||
cur = conn.execute("""
|
||||
INSERT OR IGNORE INTO holding_strategies
|
||||
(code, name, price, entry_low, entry_high, stop_loss, take_profit,
|
||||
timing_signal, action, decision_type, strategy_type, status,
|
||||
rr_ratio, stock_category, created_at, updated_at,
|
||||
sector_context, quality_check)
|
||||
VALUES (?,?,?,?,?,?,?,?,?,'自选策略','scan',
|
||||
'active',0,'关注',?,?,'', 'pending')
|
||||
""", (code, name, 0, el, eh, sl, tp, timing_signal, action, now, now))
|
||||
newly_added = cur.rowcount > 0
|
||||
|
||||
conn.execute("UPDATE candidates SET promoted=1 WHERE code=?", (code,))
|
||||
if newly_added:
|
||||
promoted += 1
|
||||
print(f" ✅ {code} {name} 评分{score} → 已加入自选({timing_signal})", flush=True)
|
||||
else:
|
||||
print(f" ⏭ {code} {name} 已在自选策略中，标记promoted", flush=True)
|
||||
|
||||
# 触发全量重评（生成完整9维策略）——仅新插入的股票需要
|
||||
if newly_added:
|
||||
try:
|
||||
import subprocess as _sp
|
||||
r = _sp.run(["python3", "/home/hmo/MoFin/scripts/per_stock_reassess.py", code],
|
||||
capture_output=True, text=True, timeout=60)
|
||||
if r.returncode == 0:
|
||||
print(f" 重评完成", flush=True)
|
||||
else:
|
||||
print(f" 重评失败: {r.stderr.strip()[:100]}", flush=True)
|
||||
except Exception as e:
|
||||
print(f" 重评异常: {e}", flush=True)
|
||||
|
||||
conn.commit()
|
||||
print(f"\n[PROMOTE] 本次提拔{promoted}只", flush=True)
|
||||
|
||||
# 推XMPP
|
||||
if promoted > 0:
|
||||
try:
|
||||
import urllib.request
|
||||
msg = f"📈 自动提拔{promoted}只候选入自选"
|
||||
payload = json.dumps({"to": "hmo@yoin.fun", "body": msg, "type": "chat"}).encode()
|
||||
req = urllib.request.Request("http://127.0.0.1:5805/", data=payload,
|
||||
headers={"Content-Type": "application/json"})
|
||||
urllib.request.urlopen(req, timeout=5)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
conn.close()
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
#!/usr/bin/env python3
|
||||
"""promote_candidates.py — 自动提拔候选股入自选
|
||||
|
||||
从 candidates 表读未提拔的候选，评估后自动加入 holding_strategies。
|
||||
"""
|
||||
import sys, json, sqlite3
|
||||
from pathlib import Path
|
||||
from datetime import datetime
|
||||
|
||||
DB_PATH = Path("/home/hmo/MoFin/data/mofin.db")
|
||||
|
||||
def main():
|
||||
conn = sqlite3.connect(str(DB_PATH))
|
||||
conn.row_factory = sqlite3.Row
|
||||
|
||||
# 读未提拔候选（按评分降序）
|
||||
rows = conn.execute("""
|
||||
SELECT c.code, c.name, c.score_final, c.entry_range, c.stop_loss, c.target
|
||||
FROM candidates c
|
||||
WHERE (c.promoted IS NULL OR c.promoted = 0)
|
||||
AND (c.dropped IS NULL OR c.dropped = 0)
|
||||
AND c.score_final >= 4
|
||||
ORDER BY c.score_final DESC
|
||||
""").fetchall()
|
||||
|
||||
if not rows:
|
||||
print("[PROMOTE] 无待提拔候选")
|
||||
conn.close()
|
||||
return
|
||||
|
||||
promoted = 0
|
||||
for r in rows:
|
||||
code = str(r[0])
|
||||
name = r[1] or code
|
||||
score = r[2] or 0
|
||||
entry_range = r[3] or ""
|
||||
sl = r[4] or 0
|
||||
tp = r[5] or 0
|
||||
|
||||
# 解析 entry_range
|
||||
el, eh = 0, 0
|
||||
if "~" in entry_range:
|
||||
parts = entry_range.split("~")
|
||||
try:
|
||||
el = float(parts[0])
|
||||
eh = float(parts[1])
|
||||
except: pass
|
||||
|
||||
# 查是否已在 holding_strategies
|
||||
exists = conn.execute(
|
||||
"SELECT id FROM holding_strategies WHERE code=? AND status='active'",
|
||||
(code,)
|
||||
).fetchone()
|
||||
if exists:
|
||||
conn.execute("UPDATE candidates SET promoted=1 WHERE code=?", (code,))
|
||||
print(f" ⏭ {code} {name} 已在自选中，标记promoted")
|
||||
continue
|
||||
|
||||
# 验证实时价格：无有效价格的候选股不入自选（防假数据污染）
|
||||
try:
|
||||
import subprocess, json as _jj
|
||||
_r = subprocess.run(["python3", "/home/hmo/.hermes/profiles/position-analyst/scripts/stock_quote.py", code],
|
||||
capture_output=True, text=True, timeout=10)
|
||||
_q = _jj.loads(_r.stdout)
|
||||
if float(_q.get("price", 0)) <= 0:
|
||||
print(f" ⏭ {code} {name} 无实时价格，跳过")
|
||||
continue
|
||||
except Exception as _e:
|
||||
print(f" ⏭ {code} {name} 价格获取失败({_e})，跳过")
|
||||
continue
|
||||
|
||||
# 构建策略
|
||||
now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
||||
timing_signal = "买入" if score >= 7 else "关注"
|
||||
price_est = (el + eh) / 2 if el > 0 and eh > 0 else 0
|
||||
reason_text = []
|
||||
if el > 0: reason_text.append(f"买{el}~{eh}")
|
||||
if sl > 0: reason_text.append(f"损{sl}")
|
||||
if tp > 0: reason_text.append(f"盈{tp}")
|
||||
if sl > 0 and tp > 0 and price_est > 0:
|
||||
rr = (tp - price_est) / (price_est - sl) if (price_est - sl) > 0 else 0
|
||||
reason_text.append(f"RR{rr:.1f}")
|
||||
reason_text.append(f"评分{score}")
|
||||
action = " | ".join(reason_text) if reason_text else f"市场扫描发现(评分{score})"
|
||||
|
||||
conn.execute("""
|
||||
INSERT INTO holding_strategies
|
||||
(code, name, price, entry_low, entry_high, stop_loss, take_profit,
|
||||
timing_signal, action, decision_type, strategy_type, status,
|
||||
rr_ratio, stock_category, created_at, updated_at,
|
||||
sector_context, quality_check)
|
||||
VALUES (?,?,?,?,?,?,?,?,?,'自选策略','scan',
|
||||
'active',0,'关注',?,?,'', 'pending')
|
||||
""", (code, name, 0, el, eh, sl, tp, timing_signal, action, now, now))
|
||||
|
||||
conn.execute("UPDATE candidates SET promoted=1 WHERE code=?", (code,))
|
||||
promoted += 1
|
||||
print(f" ✅ {code} {name} 评分{score} → 已加入自选({timing_signal})", flush=True)
|
||||
|
||||
# 触发全量重评（生成完整9维策略）
|
||||
try:
|
||||
import subprocess as _sp
|
||||
r = _sp.run(["python3", "/home/hmo/MoFin/scripts/per_stock_reassess.py", code],
|
||||
capture_output=True, text=True, timeout=60)
|
||||
if r.returncode == 0:
|
||||
print(f" 重评完成", flush=True)
|
||||
else:
|
||||
print(f" 重评失败: {r.stderr.strip()[:100]}", flush=True)
|
||||
except Exception as e:
|
||||
print(f" 重评异常: {e}", flush=True)
|
||||
|
||||
conn.commit()
|
||||
print(f"\n[PROMOTE] 本次提拔{promoted}只", flush=True)
|
||||
|
||||
# 推XMPP
|
||||
if promoted > 0:
|
||||
try:
|
||||
import urllib.request
|
||||
msg = f"📈 自动提拔{promoted}只候选入自选"
|
||||
payload = json.dumps({"to": "hmo@yoin.fun", "body": msg, "type": "chat"}).encode()
|
||||
req = urllib.request.Request("http://127.0.0.1:5805/", data=payload,
|
||||
headers={"Content-Type": "application/json"})
|
||||
urllib.request.urlopen(req, timeout=5)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
conn.close()
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
||||
Reference in New Issue
Block a user