仿alphaarena项目增加A股ai自动量化
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oficcejo
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"""
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测试Tushare数据源是否能满足AI盯盘监控要求
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测试内容：
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1. 实时行情数据获取
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2. 技术指标计算
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3. K线图数据获取
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"""
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import logging
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import os
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from dotenv import load_dotenv
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# 设置日志
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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)
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# 加载环境变量
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load_dotenv()
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def test_tushare_token():
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"""测试Tushare Token是否配置"""
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token = os.getenv('TUSHARE_TOKEN', '')
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if token:
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print(f"✅ Tushare Token已配置: {token[:10]}...")
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return True
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else:
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print("❌ Tushare Token未配置")
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return False
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def test_realtime_quote(stock_code='000063'):
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"""测试实时行情获取（Tushare降级）"""
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print(f"\n{'='*60}")
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print(f"测试1: 实时行情数据 - {stock_code}")
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print(f"{'='*60}")
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from smart_monitor_data import SmartMonitorDataFetcher
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fetcher = SmartMonitorDataFetcher()
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# 强制使用Tushare（模拟AKShare失败）
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print("正在通过Tushare获取实时行情...")
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quote = fetcher._get_realtime_quote_from_tushare(stock_code)
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if quote:
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print("✅ 实时行情获取成功！")
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print(f" 股票名称: {quote.get('stock_name', 'N/A')}")
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print(f" 当前价格: ¥{quote.get('current_price', 0):.2f}")
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print(f" 涨跌幅: {quote.get('change_pct', 0):+.2f}%")
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print(f" 成交量: {quote.get('volume', 0):,}手")
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print(f" 换手率: {quote.get('turnover_rate', 0):.2f}%")
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print(f" 数据来源: {quote.get('data_source', 'N/A')}")
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return True
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else:
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print("❌ 实时行情获取失败")
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return False
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def test_technical_indicators(stock_code='000063'):
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"""测试技术指标计算（Tushare降级）"""
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print(f"\n{'='*60}")
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print(f"测试2: 技术指标计算 - {stock_code}")
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print(f"{'='*60}")
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from smart_monitor_data import SmartMonitorDataFetcher
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fetcher = SmartMonitorDataFetcher()
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# 强制使用Tushare
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print("正在通过Tushare获取历史数据并计算技术指标...")
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indicators = fetcher._get_technical_indicators_from_tushare(stock_code)
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if indicators:
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print("✅ 技术指标计算成功！")
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print(f"\n均线系统:")
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print(f" MA5: {indicators.get('ma5', 0):.2f}")
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print(f" MA20: {indicators.get('ma20', 0):.2f}")
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print(f" MA60: {indicators.get('ma60', 0):.2f}")
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print(f" 趋势: {indicators.get('trend', 'N/A')}")
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print(f"\nMACD指标:")
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print(f" DIF: {indicators.get('macd_dif', 0):.4f}")
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print(f" DEA: {indicators.get('macd_dea', 0):.4f}")
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print(f" MACD: {indicators.get('macd', 0):.4f}")
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print(f"\nRSI指标:")
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print(f" RSI6: {indicators.get('rsi6', 0):.2f}")
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print(f" RSI12: {indicators.get('rsi12', 0):.2f}")
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print(f" RSI24: {indicators.get('rsi24', 0):.2f}")
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print(f"\nKDJ指标:")
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print(f" K: {indicators.get('kdj_k', 0):.2f}")
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print(f" D: {indicators.get('kdj_d', 0):.2f}")
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print(f" J: {indicators.get('kdj_j', 0):.2f}")
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print(f"\n布林带:")
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print(f" 上轨: {indicators.get('boll_upper', 0):.2f}")
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print(f" 中轨: {indicators.get('boll_mid', 0):.2f}")
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print(f" 下轨: {indicators.get('boll_lower', 0):.2f}")
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print(f" 位置: {indicators.get('boll_position', 'N/A')}")
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return True
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else:
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print("❌ 技术指标计算失败")
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return False
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def test_kline_data(stock_code='000063'):
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"""测试K线图数据获取（Tushare降级）"""
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print(f"\n{'='*60}")
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print(f"测试3: K线图数据 - {stock_code}")
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print(f"{'='*60}")
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from smart_monitor_kline import SmartMonitorKline
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from smart_monitor_data import SmartMonitorDataFetcher
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kline = SmartMonitorKline()
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fetcher = SmartMonitorDataFetcher()
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# 使用Tushare获取K线数据
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print("正在通过Tushare获取K线数据（60天）...")
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df = kline._get_kline_from_tushare(stock_code, days=60, ts_pro=fetcher.ts_pro)
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if df is not None and not df.empty:
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print(f"✅ K线数据获取成功！")
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print(f" 数据条数: {len(df)}条")
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print(f" 日期范围: {df['日期'].min()} ~ {df['日期'].max()}")
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print(f"\n数据列:")
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for col in df.columns:
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print(f" - {col}")
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print(f"\n最近5条数据预览:")
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print(df.tail(5)[['日期', '开盘', '最高', '最低', '收盘', '成交量']].to_string())
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return True
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else:
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print("❌ K线数据获取失败")
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return False
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def test_full_monitoring_flow(stock_code='000063'):
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"""测试完整的监控流程（使用Tushare）"""
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print(f"\n{'='*60}")
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print(f"测试4: 完整监控流程 - {stock_code}")
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print(f"{'='*60}")
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from smart_monitor_data import SmartMonitorDataFetcher
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fetcher = SmartMonitorDataFetcher()
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# 1. 获取实时行情
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print("\n步骤1: 获取实时行情...")
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quote = fetcher.get_realtime_quote(stock_code, retry=1)
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if not quote:
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print(" ❌ 实时行情获取失败")
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return False
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print(f" ✅ 当前价: ¥{quote.get('current_price', 0):.2f}")
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# 2. 计算技术指标
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print("\n步骤2: 计算技术指标...")
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indicators = fetcher.get_technical_indicators(stock_code, retry=1)
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if not indicators:
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print(" ❌ 技术指标计算失败")
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return False
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print(f" ✅ MA5: {indicators.get('ma5', 0):.2f}, 趋势: {indicators.get('trend', 'N/A')}")
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# 3. 综合数据
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print("\n步骤3: 获取综合数据...")
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comprehensive_data = fetcher.get_comprehensive_data(stock_code)
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if not comprehensive_data:
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print(" ❌ 综合数据获取失败")
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return False
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print(" ✅ 综合数据包含:")
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print(f" - 实时行情: {comprehensive_data.get('realtime_quote') is not None}")
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print(f" - 技术指标: {comprehensive_data.get('technical_indicators') is not None}")
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print("\n✅ 完整监控流程测试通过！")
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print(" Tushare可以满足AI盯盘的监控要求")
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return True
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def main():
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"""主测试函数"""
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print("="*60)
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print("Tushare数据源监控能力测试")
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print("="*60)
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# 检查Token
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if not test_tushare_token():
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print("\n❌ 请在.env文件中配置TUSHARE_TOKEN")
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return
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# 测试股票代码
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test_stock = '000063' # 中兴通讯
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results = []
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# 测试1: 实时行情
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results.append(("实时行情获取", test_realtime_quote(test_stock)))
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# 测试2: 技术指标
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results.append(("技术指标计算", test_technical_indicators(test_stock)))
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# 测试3: K线数据
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results.append(("K线图数据", test_kline_data(test_stock)))
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# 测试4: 完整流程
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results.append(("完整监控流程", test_full_monitoring_flow(test_stock)))
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# 汇总结果
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print(f"\n{'='*60}")
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print("测试结果汇总")
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print(f"{'='*60}")
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for test_name, result in results:
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status = "✅ 通过" if result else "❌ 失败"
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print(f"{test_name:20} {status}")
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all_passed = all(result for _, result in results)
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if all_passed:
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print(f"\n{'='*60}")
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print("🎉 所有测试通过！")
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print(f"{'='*60}")
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print("✅ Tushare完全可以满足AI盯盘的监控要求")
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print("✅ 数据源降级策略工作正常")
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print("✅ 可以在AKShare IP被封时使用Tushare作为备用")
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print("\n建议:")
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print("1. 保持Tushare Token配置在.env文件中")
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print("2. AKShare重试次数已设置为1次，减少IP封禁风险")
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print("3. Tushare 10000积分可以支持日常监控需求")
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else:
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print(f"\n{'='*60}")
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print("⚠️ 部分测试失败")
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print(f"{'='*60}")
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print("请检查:")
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print("1. Tushare Token是否有效")
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print("2. Tushare积分是否足够")
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print("3. 网络连接是否正常")
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if __name__ == '__main__':
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main()
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