151 lines
5.2 KiB
Python
151 lines
5.2 KiB
Python
#!/usr/bin/env python3
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"""
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诊断板块资金异动检测
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检查为什么没有找到异动板块
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"""
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import asyncio
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import sys
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import os
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from datetime import datetime, timedelta
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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from app.utils.logger import logger
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from app.config import get_settings
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from app.astock_agent.tushare_client import get_tushare_client
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async def diagnose_sector_detection():
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"""诊断板块检测"""
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print("\n" + "=" * 80)
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print("🔍 板块资金异动诊断")
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print("=" * 80)
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settings = get_settings()
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ts_client = get_tushare_client(settings.tushare_token)
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# 获取热门概念板块
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print("\n【第一步】获取热门概念板块...")
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hot_concept_sectors = [
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'人工智能', '新能源汽车', '芯片', '半导体', '5G',
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'智能电网', '物联网', '云计算', '大数据', '区块链'
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]
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sectors_df = ts_client.get_concept_sectors()
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# 找到热门板块
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hot_sectors_codes = []
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for hot_name in hot_concept_sectors:
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matches = sectors_df[sectors_df['name'].str.contains(hot_name, na=False)]
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if not matches.empty:
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for _, row in matches.iterrows():
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hot_sectors_codes.append({
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'ts_code': row['ts_code'],
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'name': row['name']
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})
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print(f"✓ 找到 {len(hot_sectors_codes)} 个热门板块")
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# 检查这些板块的资金异动
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print("\n【第二步】检查板块资金异动（量比、额比、涨幅）...")
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print("=" * 80)
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today = datetime.now().strftime('%Y%m%d')
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yesterday = (datetime.now() - timedelta(days=10)).strftime('%Y%m%d')
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# 宽松模式的阈值
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vol_threshold = 1.5
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amount_threshold = 1.3
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min_change = 0.5
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qualified_sectors = []
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for sector_info in hot_sectors_codes[:15]: # 只检查前15个
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ts_code = sector_info['ts_code']
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name = sector_info['name']
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try:
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daily_df = ts_client.pro.ths_daily(
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ts_code=ts_code,
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start_date=yesterday,
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end_date=today
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)
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if daily_df.empty or len(daily_df) < 2:
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print(f" ⚠️ {name}: 数据不足")
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continue
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daily_df = daily_df.sort_values('trade_date')
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latest = daily_df.iloc[-1]
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prev = daily_df.iloc[-2]
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latest_vol = float(latest.get('vol', 0))
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latest_avg_price = float(latest.get('avg_price', 0))
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latest_amount = latest_vol * latest_avg_price * 100 # 估算成交额
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prev_vol = float(prev.get('vol', 0))
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prev_avg_price = float(prev.get('avg_price', 0))
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prev_amount = prev_vol * prev_avg_price * 100
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change_pct = float(latest.get('pct_change', 0))
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# 计算量比和额比
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vol_ratio = latest_vol / prev_vol if prev_vol > 0 else 0
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amount_ratio = latest_amount / prev_amount if prev_amount > 0 else 0
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# 判断是否符合条件
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is_volume_surge = vol_ratio >= vol_threshold
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is_amount_surge = amount_ratio >= amount_threshold
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has_min_change = change_pct >= min_change
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is_qualified = (is_volume_surge or is_amount_surge) and has_min_change
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# 显示结果
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status = "✅" if is_qualified else "❌"
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vol_status = "🔥" if is_volume_surge else "📊"
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amount_status = "🔥" if is_amount_surge else "📊"
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change_status = "✓" if has_min_change else "✗"
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print(f" {status} {name}")
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print(f" 涨跌幅: {change_pct:+.2f}% {change_status}")
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print(f" 量比: {vol_ratio:.2f}x {vol_status} (需要≥{vol_threshold})")
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print(f" 额比: {amount_ratio:.2f}x {amount_status} (需要≥{amount_threshold})")
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if is_qualified:
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qualified_sectors.append({
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'name': name,
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'change_pct': change_pct,
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'vol_ratio': vol_ratio,
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'amount_ratio': amount_ratio
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})
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except Exception as e:
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print(f" ❌ {name}: 查询失败 ({e})")
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continue
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print("\n" + "=" * 80)
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print(f"【结果】找到 {len(qualified_sectors)} 个符合资金异动条件的板块")
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if len(qualified_sectors) == 0:
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print("\n⚠️ 没有板块符合条件，可能原因：")
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print(" 1. 市场整体资金流入不足（量比、额比都未达标）")
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print(" 2. 板块涨幅不够（需要≥0.5%）")
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print(" 3. 阈值设置过高（当前：量比≥1.5，额比≥1.3）")
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print("\n建议放宽阈值：")
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print(" - 量比阈值: 1.5 → 1.2")
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print(" - 额比阈值: 1.3 → 1.1")
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print(" - 最小涨幅: 0.5% → 0.3%")
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else:
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print("\n✅ 符合条件的板块：")
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for idx, sector in enumerate(qualified_sectors, 1):
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print(f" {idx}. {sector['name']}: {sector['change_pct']:+.2f}%, "
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f"量比{sector['vol_ratio']:.2f}x, 额比{sector['amount_ratio']:.2f}x")
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print("=" * 80)
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async def main():
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await diagnose_sector_detection()
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if __name__ == "__main__":
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asyncio.run(main())
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