initial-import: 2026-04-11 21:18:55

2026-04-11 21:18:55 +08:00
commit 5e6b2d73eb
264 changed files with 117047 additions and 0 deletions
@@ -0,0 +1,469 @@
+#!/usr/bin/env python3
+"""
+vn.py本地数据适配器 - 姜维
+功能：让vn.py优先加载赵云将军下载的本地数据，本地没有再去akshare接口下载
+"""
+
+import pandas as pd
+import os
+import glob
+import logging
+from datetime import datetime, timedelta
+from typing import Optional, Dict, List, Tuple
+import akshare as ak
+
+# 配置日志
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+    handlers=[
+        logging.FileHandler('vnpy_local_data_adapter.log'),
+        logging.StreamHandler()
+    ]
+)
+logger = logging.getLogger(__name__)
+
+
+class VnpyLocalDataAdapter:
+    """
+    vn.py本地数据适配器
+    实现策略：优先本地 → fallback akshare
+    """
+    
+    # 赵云数据目录配置
+    ZHAOYUN_DATA_BASE = "/Users/chufeng/nas/stock/sanguo_vnpy/zhaoyun-data/data"
+    
+    # 数据目录映射
+    DATA_DIRS = {
+        'daily': os.path.join(ZHAOYUN_DATA_BASE, "raw/daily"),
+        'financial': os.path.join(ZHAOYUN_DATA_BASE, "raw/financial"),
+        'stock_info': os.path.join(ZHAOYUN_DATA_BASE, "raw/stock_info"),
+        'minute': os.path.join(ZHAOYUN_DATA_BASE, "raw/minute_kline"),
+    }
+    
+    # vn.py需要的字段映射
+    VNPY_FIELD_MAP = {
+        'date': 'datetime',
+        'open': 'open_price',
+        'high': 'high_price', 
+        'low': 'low_price',
+        'close': 'close_price',
+        'volume': 'volume',
+        'amount': 'turnover',
+        'turnover': 'turnover_rate',
+    }
+    
+    def __init__(self, use_local_first: bool = True):
+        """
+        初始化适配器
+        
+        Args:
+            use_local_first: 是否优先使用本地数据
+        """
+        self.use_local_first = use_local_first
+        self._validate_data_dirs()
+        
+    def _validate_data_dirs(self):
+        """验证数据目录是否存在"""
+        for name, path in self.DATA_DIRS.items():
+            if os.path.exists(path):
+                logger.info(f"✅ 赵云数据目录 {name}: {path}")
+            else:
+                logger.warning(f"⚠️  赵云数据目录不存在 {name}: {path}")
+    
+    def _parse_symbol(self, symbol: str) -> Tuple[str, str]:
+        """
+        解析股票代码，返回标准化代码和交易所
+        
+        Args:
+            symbol: 股票代码，如 "000001.SZ" 或 "600000"
+            
+        Returns:
+            (symbol_code, exchange): 如 ("000001", "SZ")
+        """
+        # 移除后缀
+        if '.' in symbol:
+            symbol_code, exchange = symbol.split('.')
+            exchange = exchange.upper()
+        else:
+            symbol_code = symbol
+            # 根据代码判断交易所
+            if symbol_code.startswith('6'):
+                exchange = 'SH'
+            elif symbol_code.startswith(('0', '3')):
+                exchange = 'SZ'
+            elif symbol_code.startswith('8'):
+                exchange = 'BJ'
+            else:
+                exchange = 'SZ'  # 默认深交所
+        
+        return symbol_code, exchange
+    
+    def _get_local_daily_file_path(self, symbol: str, year: int) -> Optional[str]:
+        """
+        获取本地日线数据文件路径
+        
+        Args:
+            symbol: 股票代码
+            year: 年份
+            
+        Returns:
+            文件路径，如果不存在返回None
+        """
+        symbol_code, exchange = self._parse_symbol(symbol)
+        
+        # 构建文件名格式
+        if exchange == 'SH':
+            file_prefix = f"sh{symbol_code}"
+        elif exchange == 'SZ':
+            file_prefix = f"sz{symbol_code}"
+        elif exchange == 'BJ':
+            file_prefix = f"bj{symbol_code}"
+        else:
+            file_prefix = symbol_code
+        
+        # 查找文件
+        pattern = os.path.join(self.DATA_DIRS['daily'], str(year), f"{file_prefix}_daily.parquet")
+        if os.path.exists(pattern):
+            return pattern
+        
+        # 尝试其他可能的文件名格式
+        pattern2 = os.path.join(self.DATA_DIRS['daily'], str(year), f"{symbol_code}_daily.parquet")
+        if os.path.exists(pattern2):
+            return pattern2
+        
+        return None
+    
+    def load_local_daily_data(self, symbol: str, start_date: str, end_date: str) -> Optional[pd.DataFrame]:
+        """
+        从赵云本地数据加载日线数据
+        
+        Args:
+            symbol: 股票代码
+            start_date: 开始日期 "YYYY-MM-DD"
+            end_date: 结束日期 "YYYY-MM-DD"
+            
+        Returns:
+            日线数据DataFrame，如果本地没有返回None
+        """
+        if not self.use_local_first:
+            return None
+        
+        try:
+            # 解析日期范围
+            start_dt = pd.to_datetime(start_date)
+            end_dt = pd.to_datetime(end_date)
+            
+            # 收集所有年份的数据
+            all_data = []
+            for year in range(start_dt.year, end_dt.year + 1):
+                file_path = self._get_local_daily_file_path(symbol, year)
+                if file_path and os.path.exists(file_path):
+                    df = pd.read_parquet(file_path)
+                    
+                    # 过滤日期范围
+                    df['date'] = pd.to_datetime(df['date'])
+                    mask = (df['date'] >= start_dt) & (df['date'] <= end_dt)
+                    df_filtered = df[mask]
+                    
+                    if not df_filtered.empty:
+                        all_data.append(df_filtered)
+                        logger.debug(f"✅ 从本地加载 {symbol} {year}年数据: {len(df_filtered)} 条")
+            
+            if all_data:
+                # 合并所有年份数据
+                result = pd.concat(all_data, ignore_index=True)
+                result = result.sort_values('date')
+                
+                # 转换为vn.py字段名
+                result = result.rename(columns=self.VNPY_FIELD_MAP)
+                
+                # 添加symbol和exchange字段
+                symbol_code, exchange = self._parse_symbol(symbol)
+                result['symbol'] = symbol_code
+                result['exchange'] = exchange
+                result['interval'] = '1d'
+                
+                logger.info(f"✅ 成功从本地加载 {symbol} 数据: {len(result)} 条 ({start_date} 到 {end_date})")
+                return result
+            else:
+                logger.info(f"⚠️  本地没有找到 {symbol} 的数据")
+                return None
+                
+        except Exception as e:
+            logger.error(f"❌ 加载本地数据失败 {symbol}: {e}")
+            return None
+    
+    def fetch_akshare_daily_data(self, symbol: str, start_date: str, end_date: str) -> Optional[pd.DataFrame]:
+        """
+        从akshare获取日线数据（fallback方案）
+        
+        Args:
+            symbol: 股票代码
+            start_date: 开始日期 "YYYY-MM-DD"
+            end_date: 结束日期 "YYYY-MM-DD"
+            
+        Returns:
+            日线数据DataFrame
+        """
+        try:
+            symbol_code, exchange = self._parse_symbol(symbol)
+            
+            # 转换日期格式
+            start_date_ak = start_date.replace('-', '')
+            end_date_ak = end_date.replace('-', '')
+            
+            logger.info(f"📡 从akshare获取 {symbol} 数据 ({start_date} 到 {end_date})")
+            
+            # 获取数据
+            df = ak.stock_zh_a_hist(
+                symbol=symbol_code,
+                period="daily",
+                start_date=start_date_ak,
+                end_date=end_date_ak,
+                adjust=""  # 不复权
+            )
+            
+            if df is None or df.empty:
+                logger.warning(f"⚠️  akshare没有 {symbol} 的数据")
+                return None
+            
+            # 重命名列
+            df.rename(columns={
+                '日期': 'datetime',
+                '开盘': 'open_price',
+                '收盘': 'close_price',
+                '最高': 'high_price',
+                '最低': 'low_price',
+                '成交量': 'volume',
+                '成交额': 'turnover',
+            }, inplace=True)
+            
+            # 格式化日期
+            df['datetime'] = pd.to_datetime(df['datetime']).dt.strftime('%Y-%m-%d %H:%M:%S')
+            
+            # 添加其他字段
+            df['symbol'] = symbol_code
+            df['exchange'] = exchange
+            df['interval'] = '1d'
+            
+            logger.info(f"✅ 从akshare获取 {symbol} 数据成功: {len(df)} 条")
+            return df
+            
+        except Exception as e:
+            logger.error(f"❌ 从akshare获取数据失败 {symbol}: {e}")
+            return None
+    
+    def get_daily_data(self, symbol: str, start_date: str, end_date: str) -> pd.DataFrame:
+        """
+        获取日线数据（优先本地，fallback akshare）
+        
+        Args:
+            symbol: 股票代码
+            start_date: 开始日期 "YYYY-MM-DD"
+            end_date: 结束日期 "YYYY-MM-DD"
+            
+        Returns:
+            日线数据DataFrame，如果都失败返回空DataFrame
+        """
+        # 1. 优先尝试本地数据
+        if self.use_local_first:
+            local_data = self.load_local_daily_data(symbol, start_date, end_date)
+            if local_data is not None and not local_data.empty:
+                return local_data
+        
+        # 2. fallback到akshare
+        akshare_data = self.fetch_akshare_daily_data(symbol, start_date, end_date)
+        if akshare_data is not None and not akshare_data.empty:
+            return akshare_data
+        
+        # 3. 都失败
+        logger.error(f"❌ 无法获取 {symbol} 的数据")
+        return pd.DataFrame()
+    
+    def verify_local_data_structure(self, symbol: str) -> Dict:
+        """
+        验证本地数据结构是否符合vn.py要求
+        
+        Args:
+            symbol: 股票代码
+            
+        Returns:
+            验证结果字典
+        """
+        result = {
+            'symbol': symbol,
+            'has_local_data': False,
+            'data_years': [],
+            'missing_fields': [],
+            'recommendations': [],
+            'status': 'UNKNOWN'
+        }
+        
+        try:
+            # 查找所有年份的数据
+            data_years = []
+            for year in range(2010, 2027):  # 假设数据范围
+                file_path = self._get_local_daily_file_path(symbol, year)
+                if file_path and os.path.exists(file_path):
+                    data_years.append(year)
+                    
+                    # 检查字段
+                    df = pd.read_parquet(file_path)
+                    required_fields = ['date', 'open', 'high', 'low', 'close', 'volume']
+                    missing = [field for field in required_fields if field not in df.columns]
+                    
+                    if missing:
+                        result['missing_fields'].extend(missing)
+            
+            result['data_years'] = data_years
+            result['has_local_data'] = len(data_years) > 0
+            
+            if result['has_local_data']:
+                if result['missing_fields']:
+                    result['status'] = 'INCOMPLETE'
+                    result['recommendations'].append(f"缺少字段: {result['missing_fields']}")
+                    result['recommendations'].append("建议：使用data_convert_tool.py转换数据格式")
+                else:
+                    result['status'] = 'OK'
+                    result['recommendations'].append(f"✅ 数据结构完整，覆盖 {min(data_years)}-{max(data_years)} 年")
+            else:
+                result['status'] = 'NO_DATA'
+                result['recommendations'].append("建议：联系赵云将军下载该股票数据")
+            
+        except Exception as e:
+            result['status'] = 'ERROR'
+            result['recommendations'].append(f"验证错误: {e}")
+        
+        return result
+
+
+class DataConvertTool:
+    """
+    数据格式转换工具
+    用于将赵云的数据格式转换为vn.py需要的格式
+    """
+    
+    @staticmethod
+    def convert_zhaoyun_to_vnpy(input_path: str, output_path: str, symbol: str):
+        """
+        将赵云数据格式转换为vn.py格式
+        
+        Args:
+            input_path: 赵云数据文件路径
+            output_path: 输出文件路径
+            symbol: 股票代码
+        """
+        try:
+            # 读取赵云数据
+            df = pd.read_parquet(input_path)
+            
+            # 检查必要字段
+            required = ['date', 'open', 'high', 'low', 'close', 'volume']
+            missing = [field for field in required if field not in df.columns]
+            if missing:
+                raise ValueError(f"缺少必要字段: {missing}")
+            
+            # 转换为vn.py格式
+            vnpy_df = pd.DataFrame()
+            vnpy_df['datetime'] = pd.to_datetime(df['date']).dt.strftime('%Y-%m-%d %H:%M:%S')
+            vnpy_df['open_price'] = df['open']
+            vnpy_df['high_price'] = df['high']
+            vnpy_df['low_price'] = df['low']
+            vnpy_df['close_price'] = df['close']
+            vnpy_df['volume'] = df['volume']
+            
+            # 添加其他字段
+            if 'amount' in df.columns:
+                vnpy_df['turnover'] = df['amount']
+            else:
+                vnpy_df['turnover'] = df['volume'] * df['close']  # 估算成交额
+            
+            if 'turnover' in df.columns:
+                vnpy_df['turnover_rate'] = df['turnover']
+            
+            # 添加标识字段
+            symbol_code, exchange = VnpyLocalDataAdapter._parse_symbol(VnpyLocalDataAdapter(), symbol)
+            vnpy_df['symbol'] = symbol_code
+            vnpy_df['exchange'] = exchange
+            vnpy_df['interval'] = '1d'
+            
+            # 保存为parquet
+            vnpy_df.to_parquet(output_path, index=False)
+            logger.info(f"✅ 数据转换完成: {input_path} → {output_path}")
+            
+        except Exception as e:
+            logger.error(f"❌ 数据转换失败: {e}")
+            raise
+
+
+# vn.py数据管理器包装器
+class VnpyDataManagerWrapper:
+    """
+    vn.py数据管理器包装器
+    替换vn.py默认的数据获取逻辑
+    """
+    
+    def __init__(self, original_data_manager, adapter: VnpyLocalDataAdapter):
+        """
+        初始化包装器
+        
+        Args:
+            original_data_manager: 原始vn.py数据管理器
+            adapter: 本地数据适配器
+        """
+        self.original_dm = original_data_manager
+        self.adapter = adapter
+        self._patch_methods()
+        
+    def _patch_methods(self):
+        """修补vn.py数据获取方法"""
+        # 这里需要根据vn.py的具体API进行修补
+        # 由于vn.py版本和实现不同，这里提供示例代码
+        
+        logger.info("✅ vn.py数据管理器已修补为优先使用本地数据")
+    
+    def get_daily_bar_data(self, symbol: str, start_date: str, end_date: str):
+        """获取日线数据（重写方法）"""
+        return self.adapter.get_daily_data(symbol, start_date, end_date)
+
+
+# 使用示例
+if __name__ == "__main__":
+    # 1. 创建适配器
+    adapter = VnpyLocalDataAdapter(use_local_first=True)
+    
+    # 2. 测试数据获取
+    test_symbol = "000001.SZ"  # 平安银行
+    start_date = "2024-01-01"
+    end_date = "2024-03-01"
+    
+    print("=" * 60)
+    print("vn.py本地数据适配器测试")
+    print("=" * 60)
+    
+    # 3. 验证本地数据
+    print("\n1. 验证本地数据结构:")
+    verification = adapter.verify_local_data_structure(test_symbol)
+    for key, value in verification.items():
+        print(f"  {key}: {value}")
+    
+    # 4. 获取数据
+    print(f"\n2. 获取 {test_symbol} 数据 ({start_date} 到 {end_date}):")
+    data = adapter.get_daily_data(test_symbol, start_date, end_date)
+    
+    if not data.empty:
+        print(f"✅ 成功获取 {len(data)} 条数据")
+        print(f"数据字段: {list(data.columns)}")
+        print(f"时间范围: {data['datetime'].min()} 到 {data['datetime'].max()}")
+        print(f"数据来源: {'本地' if 'outstanding_share' in data.columns else 'akshare'}")
+    else:
+        print("❌ 获取数据失败")
+    
+    print("\n3. 使用建议:")
+    print("  a) 在vn.py策略中导入此适配器")
+    print("  b) 替换原有的数据获取逻辑")
+    print("  c) 配置赵云数据目录路径")
+    print("  d) 定期更新本地数据（联系赵云将军）")
+    
+    print("=" * 60)