198 lines
8.7 KiB
Python
198 lines
8.7 KiB
Python
#!/usr/bin/env python3
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"""resonance.py — 三维共振层（技术×资金×消息）
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在 v7.1 闸门通过后，对买入信号做三维合成判断：
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否决(veto): 资金持续流出 + 消息利空（双重负面）
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降级(downgrade): 任一单维度负面
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共振(resonance): 资金强流入 + 消息利好
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通过(pass): 其余
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所有判断写入 signal_veto_log 供后续回测验证（2026-07-29 老爸批准）"""
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import sqlite3, json, sys
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from datetime import datetime, timedelta
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DB = "/home/hmo/MoFin/data/mofin.db"
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for p in ("/home/hmo/MoFin", "/home/hmo/web-dashboard"):
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if p not in sys.path:
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sys.path.insert(0, p)
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NEWS_NEGATIVE = {'利空', '偏空', '中性偏空'}
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NEWS_POSITIVE = {'利好', '偏多', '中性偏利好'}
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FLOW_NEG_THRESHOLD = -2.5 # v6归因：持续流出胜率仅37.5%
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FLOW_STRONG_POS_THRESHOLD = 4 # v6归因：加速流入胜率77.8%
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def _flow_state(code):
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"""资金维度: flow_5d / flow_delta → negative/neutral/positive/strong_positive"""
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try:
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conn = sqlite3.connect(DB)
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rows = conn.execute("""
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SELECT date, main_pct FROM stock_capital_flow
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WHERE code=? ORDER BY date DESC LIMIT 10
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""", (code,)).fetchall()
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conn.close()
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except sqlite3.OperationalError:
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return {'state': 'unknown', 'flow_5d': None, 'flow_delta': None}
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if len(rows) < 5:
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return {'state': 'unknown', 'flow_5d': None, 'flow_delta': None}
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recent = [r[1] for r in rows[:5] if r[1] is not None]
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prior = [r[1] for r in rows[5:10] if r[1] is not None]
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flow_5d = sum(recent) / len(recent) if recent else None
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flow_delta = None
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if recent and prior:
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flow_delta = flow_5d - sum(prior) / len(prior)
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state = 'neutral'
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if flow_5d is not None and flow_5d < FLOW_NEG_THRESHOLD:
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state = 'negative'
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elif flow_delta is not None and flow_delta > FLOW_STRONG_POS_THRESHOLD:
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state = 'strong_positive'
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elif flow_5d is not None and flow_5d > 1:
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state = 'positive'
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return {'state': state, 'flow_5d': round(flow_5d, 2) if flow_5d is not None else None,
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'flow_delta': round(flow_delta, 2) if flow_delta is not None else None}
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# ── 行业新闻情绪分析（2026-07-31：东方财富翻页新闻→500条/股）──
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_POS_KW = ['大涨','涨停','回暖','反弹','回升','领涨','突破','创新高','资金流入','净流入','加仓','密集调研','增持','回购']
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_NEG_KW = ['大跌','跌停','回落','下跌','下挫','走弱','资金流出','净流出','减持','利空','风险','预警','亏损','预警']
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def sector_news_sentiment(sector, days=3):
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import sqlite3
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conn = sqlite3.connect('/home/hmo/MoFin/data/mofin.db')
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try:
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stocks = conn.execute("SELECT code FROM stock_sectors_em WHERE sector=?", (sector,)).fetchall()
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if not stocks:
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return {'state': 'neutral', 'pos': 0, 'neg': 0, 'total': 0}
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from datetime import datetime, timedelta
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since = (datetime.now() - timedelta(days=days)).strftime('%Y-%m-%d')
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codes = tuple(s[0] for s in stocks)
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placeholders = ','.join('?' for _ in codes)
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arts = conn.execute(f"SELECT title, content FROM stock_news WHERE code IN ({placeholders}) AND date>=?", codes + (since,)).fetchall()
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pos = neg = 0
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for t, c in arts:
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text = (t or '') + ' ' + (c or '')
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for kw in _POS_KW:
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if kw in text: pos += 1; break
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for kw in _NEG_KW:
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if kw in text: neg += 1; break
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total = pos + neg
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state = 'neutral'
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if total > 0 and pos / max(total, 1) > 0.6:
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state = 'positive'
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elif total > 0 and neg / max(total, 1) > 0.6:
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state = 'negative'
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return {'state': state, 'pos': pos, 'neg': neg, 'total': total}
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except Exception:
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return {'state': 'neutral', 'pos': 0, 'neg': 0, 'total': 0}
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finally:
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conn.close()
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def _news_state(code, name=None, sector=None):
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"""消息维度: 3日内该股/该板块最新消息情绪"""
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since = (datetime.now() - timedelta(days=3)).strftime('%Y-%m-%d')
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try:
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conn = sqlite3.connect(DB)
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# 个股级优先（searched_stocks 或 summary 含代码/名称）
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rows = conn.execute("""
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SELECT overall_sentiment, summary, sector, created_at FROM signal_news
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WHERE created_at >= ? AND (
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searched_stocks LIKE ? OR summary LIKE ? OR sector = ?
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)
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ORDER BY id DESC LIMIT 10
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""", (since, f'%{code}%', f'%{name or code}%', sector or '')).fetchall()
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conn.close()
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except sqlite3.OperationalError:
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return {'state': 'unknown', 'sentiment': None, 'summary': None}
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sentiment = None
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summary = None
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for s, sm, sec, ts in rows:
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if s in NEWS_NEGATIVE or s in NEWS_POSITIVE:
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sentiment = s
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summary = (sm or '')[:120]
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break
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if sentiment is None:
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return {'state': 'neutral', 'sentiment': None, 'summary': None}
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state = 'negative' if sentiment in NEWS_NEGATIVE else 'positive'
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return {'state': state, 'sentiment': sentiment, 'summary': summary}
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def evaluate_resonance(code, gate, name=None):
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"""三维合成判断。gate = v71_gate.check_entry_gate 的返回"""
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flow = _flow_state(code)
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# 板块名：从 gate factors 拿不到名字，这里用 sector_ctx 的映射
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sector = None
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try:
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from strategy_lab import _STOCK_SECTOR
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sector = _STOCK_SECTOR.get(code)
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except Exception:
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pass
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news = _news_state(code, name, sector)
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fs, ns = flow['state'], news['state']
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if fs == 'negative' and ns == 'negative':
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decision = 'veto'
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reason = f"资金持续流出({flow['flow_5d']}) + 消息利空({news['sentiment']})"
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elif fs == 'negative':
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decision = 'downgrade'
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reason = f"资金持续流出({flow['flow_5d']})"
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elif ns == 'negative':
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decision = 'downgrade'
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reason = f"消息利空({news['sentiment']})"
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elif fs == 'strong_positive' and ns == 'positive':
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decision = 'resonance'
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reason = f"三维共振: 资金加速流入({flow['flow_delta']}) + 消息{news['sentiment']}"
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else:
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decision = 'pass'
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reason = ''
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# ── 第四维：行业新闻情绪叠加(2026-07-31) ──
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sns = sector_news_sentiment(sector) if sector else {'state': 'neutral', 'pos': 0, 'neg': 0, 'total': 0}
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if decision == 'pass' and sns['state'] == 'positive' and fs in ('positive', 'strong_positive'):
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decision = 'resonance'
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reason = f"行业新闻确认({sns['pos']}pos/{sns['neg']}neg) + 资金流入 → 共振"
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elif decision == 'pass' and sns['state'] == 'negative' and fs == 'negative':
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decision = 'downgrade'
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reason = f"行业新闻利空({sns['pos']}pos/{sns['neg']}neg) + 资金流出 → 降级"
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return {'decision': decision, 'reason': reason, 'flow': flow, 'news': news, 'sector': sector, 'sector_news': sns}
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def log_resonance(code, name, price, gate, res, signal_before, signal_after):
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"""完整记录三维状态 → signal_veto_log（后续回测验证的数据资产）"""
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conn = sqlite3.connect(DB)
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conn.execute("""
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CREATE TABLE IF NOT EXISTS signal_veto_log (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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code TEXT, name TEXT, price REAL,
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tech_score INTEGER, tech_summary TEXT,
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flow_5d REAL, flow_delta REAL, flow_state TEXT,
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news_sentiment TEXT, news_state TEXT, news_summary TEXT,
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sector TEXT,
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decision TEXT, reason TEXT,
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signal_before TEXT, signal_after TEXT,
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created_at TEXT
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)
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""")
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conn.execute("""
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INSERT INTO signal_veto_log
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(code, name, price, tech_score, tech_summary, flow_5d, flow_delta, flow_state,
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news_sentiment, news_state, news_summary, sector, decision, reason,
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signal_before, signal_after, created_at)
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VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)
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""", (code, name, price, gate.get('score'), gate.get('summary'),
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res['flow'].get('flow_5d'), res['flow'].get('flow_delta'), res['flow'].get('state'),
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res['news'].get('sentiment'), res['news'].get('state'), res['news'].get('summary'),
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res.get('sector'), res['decision'], res['reason'],
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signal_before, signal_after,
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datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
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conn.commit()
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conn.close()
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if __name__ == '__main__':
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from v71_gate import check_entry_gate
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for c in sys.argv[1:] or ['603599']:
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g = check_entry_gate(c)
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r = evaluate_resonance(c, g)
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print(f"{c}: gate={g['pass']} | 资金={r['flow']['state']}({r['flow']['flow_5d']}) "
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f"消息={r['news']['state']}({r['news']['sentiment']}) → {r['decision']} {r['reason']}")
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