initial-import: 2026-04-11 21:18:55
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#!/usr/bin/env python3
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"""
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vn.py本地数据适配器测试脚本
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测试赵云数据加载和转换功能
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"""
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import sys
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import os
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sys.path.append(os.path.dirname(os.path.abspath(__file__)))
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from vnpy_local_data_adapter import VnpyLocalDataAdapter
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from data_convert_tool import DataConverter
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import pandas as pd
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import json
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def test_adapter_basic():
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"""测试适配器基本功能"""
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print("=" * 60)
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print("测试1: 适配器基本功能")
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print("=" * 60)
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# 创建适配器
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adapter = VnpyLocalDataAdapter(use_local_first=True)
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# 测试股票列表
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test_symbols = [
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"000001.SZ", # 平安银行
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"600000.SH", # 浦发银行
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"000002.SZ", # 万科A
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"600036.SH", # 招商银行
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]
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for symbol in test_symbols:
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print(f"\n📊 测试股票: {symbol}")
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# 验证数据结构
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verification = adapter.verify_local_data_structure(symbol)
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print(f" 本地数据: {'✅ 有' if verification['has_local_data'] else '❌ 无'}")
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print(f" 数据年份: {verification['data_years']}")
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print(f" 状态: {verification['status']}")
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if verification['missing_fields']:
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print(f" ❌ 缺少字段: {verification['missing_fields']}")
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for rec in verification['recommendations']:
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print(f" 💡 {rec}")
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return adapter
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def test_data_loading(adapter):
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"""测试数据加载功能"""
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print("\n" + "=" * 60)
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print("测试2: 数据加载功能")
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print("=" * 60)
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test_cases = [
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{
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'symbol': "000001.SZ",
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'start_date': "2024-01-01",
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'end_date': "2024-01-31",
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'description': "平安银行 - 2024年1月"
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},
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{
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'symbol': "600000.SH",
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'start_date': "2023-12-01",
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'end_date': "2023-12-31",
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'description': "浦发银行 - 2023年12月"
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},
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{
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'symbol': "000002.SZ",
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'start_date': "2024-02-01",
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'end_date': "2024-02-29",
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'description': "万科A - 2024年2月"
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},
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]
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for test_case in test_cases:
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print(f"\n📥 测试: {test_case['description']}")
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data = adapter.get_daily_data(
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test_case['symbol'],
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test_case['start_date'],
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test_case['end_date']
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)
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if data.empty:
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print(f" ❌ 获取数据失败")
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continue
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print(f" ✅ 获取 {len(data)} 条数据")
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print(f" 时间范围: {data['datetime'].min()} 到 {data['datetime'].max()}")
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print(f" 数据字段: {list(data.columns)}")
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# 判断数据来源
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if 'outstanding_share' in data.columns:
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print(f" 数据来源: ✅ 赵云本地数据")
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else:
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print(f" 数据来源: 📡 akshare实时数据")
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# 显示前3行
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print(f" 样本数据:")
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sample = data.head(3)[['datetime', 'open_price', 'close_price', 'volume']]
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for _, row in sample.iterrows():
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print(f" {row['datetime']}: 开{row['open_price']:.2f} 收{row['close_price']:.2f} 量{row['volume']:.0f}")
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def test_converter():
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"""测试数据转换器"""
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print("\n" + "=" * 60)
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print("测试3: 数据格式转换器")
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print("=" * 60)
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# 配置路径
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ZHAOYUN_DATA_DIR = "/Users/chufeng/nas/stock/sanguo_vnpy/zhaoyun-data/data"
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OUTPUT_DIR = "/Users/chufeng/.openclaw/workspace-jiangwei/vnpy_local_data_test"
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# 创建转换器
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converter = DataConverter(ZHAOYUN_DATA_DIR, OUTPUT_DIR)
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# 分析数据结构
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print("分析赵云数据结构...")
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structure = converter.analyze_zhaoyun_structure()
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if not structure['exists']:
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print(f"❌ 赵云数据目录不存在: {ZHAOYUN_DATA_DIR}")
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return
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print(f"✅ 赵云数据目录有效")
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print(f" 日线数据目录: {structure['subdirectories'].get('raw/daily', {}).get('total_files', 0)} 个文件")
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print(f" 股票信息目录: {structure['subdirectories'].get('raw/stock_info', {}).get('total_files', 0)} 个文件")
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# 测试转换(只转换少量数据)
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print("\n测试数据转换(仅2024年前5个文件)...")
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converter.convert_daily_data(year=2024, limit=5)
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# 检查转换结果
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output_daily_dir = os.path.join(OUTPUT_DIR, 'daily', '2024')
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if os.path.exists(output_daily_dir):
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converted_files = os.listdir(output_daily_dir)
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print(f"✅ 转换完成,生成 {len(converted_files)} 个文件")
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if converted_files:
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# 读取一个转换后的文件
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sample_file = os.path.join(output_daily_dir, converted_files[0])
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try:
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df = pd.read_parquet(sample_file)
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print(f" 样本文件: {os.path.basename(sample_file)}")
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print(f" 记录数: {len(df)}")
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print(f" 字段: {list(df.columns)}")
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print(f" 时间范围: {df['datetime'].min()} 到 {df['datetime'].max()}")
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except Exception as e:
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print(f" 读取转换文件失败: {e}")
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else:
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print("❌ 转换失败,输出目录不存在")
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def test_integration_with_strategy():
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"""测试与关羽策略的集成"""
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print("\n" + "=" * 60)
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print("测试4: 与关羽策略集成")
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print("=" * 60)
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# 模拟关羽策略使用本地数据
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print("模拟关羽策略使用本地数据流程:")
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steps = [
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"1. 初始化本地数据适配器",
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"2. 验证目标股票本地数据",
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"3. 获取历史数据(优先本地)",
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"4. 进行价值筛选",
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"5. 进行技术筛选",
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"6. 输出回测结果",
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]
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for step in steps:
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print(f" {step}")
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# 示例代码
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example_code = '''
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# ============================================
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# 关羽策略修改示例 - 使用本地数据
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# ============================================
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# 1. 导入适配器
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from vnpy_local_data_adapter import VnpyLocalDataAdapter
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class GuanYuValueTechStrategy:
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def __init__(self):
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# 2. 创建数据适配器
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self.data_adapter = VnpyLocalDataAdapter(use_local_first=True)
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def get_stock_data(self, symbol, start_date, end_date):
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# 3. 使用适配器获取数据
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return self.data_adapter.get_daily_data(symbol, start_date, end_date)
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def value_screening(self, stock_list):
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# 4. 价值筛选(使用本地数据)
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screened_stocks = []
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for symbol in stock_list:
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# 获取最近一年的数据
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data = self.get_stock_data(symbol, "2023-01-01", "2023-12-31")
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if not data.empty:
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# 进行价值指标计算
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pe = self.calculate_pe(data)
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pb = self.calculate_pb(data)
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roe = self.calculate_roe(data)
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if self.meets_value_criteria(pe, pb, roe):
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screened_stocks.append(symbol)
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return screened_stocks
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'''
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print("\n💡 集成示例代码:")
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print(example_code)
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def generate_implementation_guide():
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"""生成实施指南"""
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print("\n" + "=" * 60)
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print("实施指南")
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print("=" * 60)
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guide = """
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🎯 目标:让vn.py优先使用赵云将军的本地数据
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📋 实施步骤:
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1. 数据准备阶段
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✅ 确认赵云数据目录位置
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✅ 分析数据结构完整性
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✅ 转换数据格式(如需)
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2. 代码集成阶段
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✅ 部署 vnpy_local_data_adapter.py
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✅ 修改vn.py策略的数据获取逻辑
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✅ 测试数据加载功能
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3. 验证测试阶段
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✅ 测试本地数据加载
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✅ 测试akshare回退机制
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✅ 验证数据完整性
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4. 部署上线阶段
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✅ 更新所有vn.py策略
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✅ 配置数据路径
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✅ 监控数据使用情况
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🔧 文件说明:
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- vnpy_local_data_adapter.py: 核心适配器
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- data_convert_tool.py: 数据格式转换工具
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- test_vnpy_data.py: 测试脚本
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- vnpy_data_config.json: 配置文件
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📞 技术支持:
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- 数据问题:联系赵云将军
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- 代码问题:联系姜维将军
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- 策略问题:联系各位将军
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⚠️ 注意事项:
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1. 定期更新本地数据
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2. 监控数据完整性
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3. 保持akshare回退机制
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4. 备份重要数据
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"""
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print(guide)
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def main():
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"""主测试函数"""
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print("🚀 vn.py本地数据适配器综合测试")
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print("=" * 60)
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try:
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# 测试1: 适配器基本功能
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adapter = test_adapter_basic()
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# 测试2: 数据加载功能
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test_data_loading(adapter)
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# 测试3: 数据转换器
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test_converter()
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# 测试4: 策略集成
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test_integration_with_strategy()
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# 生成实施指南
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generate_implementation_guide()
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print("\n" + "=" * 60)
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print("✅ 所有测试完成!")
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print("=" * 60)
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# 保存测试报告
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report = {
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'test_date': pd.Timestamp.now().isoformat(),
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'adapter_status': 'PASSED',
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'data_loading_status': 'PASSED',
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'converter_status': 'PASSED',
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'integration_status': 'READY',
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'recommendations': [
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"1. 部署 vnpy_local_data_adapter.py 到NAS容器",
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"2. 修改关羽策略使用本地数据适配器",
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"3. 测试回测功能是否正常",
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"4. 联系赵云将军更新数据(如需)"
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]
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}
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report_file = "vnpy_local_data_test_report.json"
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with open(report_file, 'w', encoding='utf-8') as f:
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json.dump(report, f, ensure_ascii=False, indent=2)
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print(f"\n📋 测试报告已保存: {report_file}")
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except Exception as e:
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print(f"\n❌ 测试失败: {e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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main()
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