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
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+#!/usr/bin/env python3
+"""
+导入赵云提供的 510300.SSE 日线数据到 vnpy sqlite 数据库
+按照赵云提供的步骤：
+1. 读取 parquet 文件
+2. 转换为 vnpy BarData
+3. 写入数据库
+"""
+
+import sys
+import types
+
+# 兼容性模块
+print("🔧 [IMPORT] 加载vnpy.app兼容性模块...")
+vnpy_app_module = types.ModuleType('vnpy.app')
+sys.modules['vnpy.app'] = vnpy_app_module
+submodules = ['cta_strategy', 'cta_backtester', 'data_manager']
+for name in submodules:
+    full_name = f'vnpy.app.{name}'
+    submodule = types.ModuleType(full_name)
+    sys.modules[full_name] = submodule
+    setattr(vnpy_app_module, name, submodule)
+
+from vnpy_ctastrategy import (
+    CtaTemplate,
+    StopOrder,
+    TickData,
+    BarData,
+    TradeData,
+    OrderData,
+    BarGenerator,
+    ArrayManager,
+)
+from vnpy.trader.constant import Direction, Offset, Interval, Exchange
+
+sys.modules['vnpy.app.cta_strategy'].CtaTemplate = CtaTemplate
+vnpy_app_module.CtaTemplate = CtaTemplate
+
+from vnpy_ctabacktester import BacktesterEngine
+sys.modules['vnpy.app.cta_backtester'].BacktesterEngine = BacktesterEngine
+vnpy_app_module.BacktesterEngine = BacktesterEngine
+
+print("✅ [IMPORT] vnpy.app兼容性模块加载完成！")
+
+import pandas as pd
+from vnpy.trader.object import BarData
+from vnpy.trader.database import get_database
+
+def main():
+    print("\n🚀 [IMPORT] 开始导入 510300.SSE 日线数据")
+    
+    # 1. 读取parquet文件
+    parquet_path = "/Users/chufeng/nas/stock-data/sanguo_quant_live/zhaoyun-data/data/raw/daily/sh510300_daily.parquet"
+    print(f"\n📖 [IMPORT] 读取数据: {parquet_path}")
+    
+    df = pd.read_parquet(parquet_path)
+    print(f"✅ [IMPORT] 读取完成，共 {len(df)} 行")
+    print(f"   时间范围: {df['trade_date'].min()} ~ {df['trade_date'].max()}")
+    print(f"   列: {list(df.columns)}")
+    
+    # 2. 转换为 vnpy BarData
+    print(f"\n🔧 [IMPORT] 转换为 BarData...")
+    bars = []
+    for idx, row in df.iterrows():
+        bar = BarData(
+            symbol="510300",
+            exchange=Exchange.SSE,
+            interval=Interval.DAILY,
+            datetime=row["trade_date"],
+            open_price=row["open"],
+            high_price=row["high"],
+            low_price=row["low"],
+            close_price=row["close"],
+            volume=row["volume"],
+            turnover=row["amount"],
+            gateway_name="DATA"
+        )
+        bars.append(bar)
+    
+    print(f"✅ [IMPORT] 转换完成，共 {len(bars)} 个BarData")
+    
+    # 3. 写入数据库
+    print(f"\n💾 [IMPORT] 写入数据库...")
+    db = get_database()
+    
+    # 先统计原有数据
+    from datetime import datetime
+    start_dt = datetime(2012, 5, 28)
+    end_dt = datetime(2026, 3, 27)
+    existing = db.load_bar_data("510300", Exchange.SSE, Interval.DAILY, start_dt, end_dt)
+    print(f"⚠️ [IMPORT] 原有数据: {len(existing)} 条在这个范围内")
+    
+    # 保存数据
+    db.save_bar_data(bars)
+    print(f"✅ [IMPORT] 保存完成，共写入 {len(bars)} 条")
+    
+    # 验证写入
+    existing_after = db.load_bar_data("510300", Exchange.SSE, Interval.DAILY, start_dt, end_dt)
+    print(f"✅ [IMPORT] 写入后验证: {len(existing_after)} 条在这个范围内")
+    
+    # 验证目标时间范围
+    print(f"\n✅ [IMPORT] 验证目标时间范围 2021-01-01 ~ 2026-03-01:")
+    start_target = datetime(2021, 1, 1)
+    end_target = datetime(2026, 3, 1)
+    target_bars = db.load_bar_data("510300", Exchange.SSE, Interval.DAILY, start_target, end_target)
+    print(f"   找到 {len(target_bars)} 条数据")
+    if len(target_bars) > 0:
+        print(f"   第一条: {target_bars[0].datetime}")
+        print(f"   最后一条: {target_bars[-1].datetime}")
+        print(f"   ✅ 满足需求！")
+    
+    print("\n🎉 [IMPORT] 导入完成！")
+
+if __name__ == '__main__':
+    main()