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 +1,102 @@
+#!/usr/bin/env python3
+"""
+在Docker容器内直接执行关羽的策略回测
+不经过HTTP API，直接在容器内运行
+"""
+
+# ============================================
+# 导入完整RPC服务代码（复用run_strategy_backtest函数）
+# ============================================
+import types
+import sys
+
+# 复制完整的RPC服务代码
+with open("/Users/chufeng/.openclaw/workspace-jiangwei/final_rpc_correct.py", 'r', encoding='utf-8') as f:
+    rpc_code = f.read()
+
+# 执行RPC服务代码，但不启动服务
+exec(rpc_code, globals())
+
+# 不会自动启动RPC服务，因为我们已经定义了run_strategy_backtest
+print("=" * 80)
+print("🚀 RPC服务代码加载完成，准备执行回测")
+print("=" * 80)
+
+# ============================================
+# 读取关羽的策略代码
+# ============================================
+risk_control_file = "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/factors-dynamic-weight-timing-20260327/risk_control.py"
+strategy_file = "/Users/chufeng/.openclaw/sanguo_projects/sanguo_quant_live/strategies/factors-dynamic-weight-timing-20260327/main_strategy_single_file.py"
+
+with open(risk_control_file, 'r', encoding='utf-8') as f:
+    risk_control_code = f.read()
+
+with open(strategy_file, 'r', encoding='utf-8') as f:
+    strategy_code = f.read()
+
+# 合并代码
+full_strategy_code = f"{risk_control_code}\n\n# ========== 主策略 ==========\n\n{strategy_code}"
+
+print(f"✅ 风控代码: {len(risk_control_code)} 字符")
+print(f"✅ 主策略代码: {len(strategy_code)} 字符")
+
+# ============================================
+# 执行回测
+# ============================================
+print("\n" + "=" * 80)
+print("开始执行回测...")
+print("=" * 80)
+
+result = run_strategy_backtest(
+    strategy_code=full_strategy_code,
+    symbol="510300.SSE",
+    interval="1d",
+    start=1609459200,  # 2021-01-01
+    end=1772515200,    # 2026-03-01
+    capital=1000000,
+    rate=3e-5,
+    slippage=0.002,
+    size=10000,
+    pricetick=0.001,
+    data_source="sqlite"
+)
+
+# ============================================
+# 打印结果
+# ============================================
+print("\n" + "=" * 80)
+print("回测结果:")
+print("=" * 80)
+
+if "error" in result:
+    print(f"❌ 回测失败: {result.get('error')}")
+    if "traceback" in result:
+        print("\n错误堆栈:")
+        print(result["traceback"])
+    sys.exit(1)
+
+if "statistics" in result:
+    stats = result["statistics"]
+    
+    print(f"\n📊 绩效指标:")
+    print(f"   总收益率: {stats.get('total_return', 0):.2%}")
+    print(f"   年化收益率: {stats.get('annual_return', 0):.2%}")
+    print(f"   最大回撤: {stats.get('max_drawdown', 0):.2%}")
+    print(f"   夏普比率: {stats.get('sharpe_ratio', 0):.2f}")
+    print(f"   总交易次数: {stats.get('total_trades', 0)}")
+    print(f"   胜率: {stats.get('win_rate', 0):.2%}")
+    print(f"   盈亏比: {stats.get('profit_loss_ratio', 0):.2f}")
+
+if "trades" in result:
+    trades = result["trades"]
+    print(f"\n📝 交易记录: 共 {len(trades)} 笔")
+    
+    for idx, trade in enumerate(trades[:10], 1):
+        print(f"   {idx}. {trade.get('datetime')} {trade.get('direction')} {trade.get('symbol')} @ {trade.get('price')} × {trade.get('volume')}")
+    
+    if len(trades) > 10:
+        print(f"   ... 还有 {len(trades) - 10} 笔")
+
+print("\n" + "=" * 80)
+print("✅ 回测执行完成！")
+print("=" * 80)