auto-sync: 2026-04-30 23:09:47

data_platform/test_catalog.py

@@ -1,5 +1,5 @@
 """
-数据平台测试 - 验证 DataCatalog 4个核心API
+数据平台完整测试 - 验证 DataCatalog + BacktestRunner
 
 运行方式：cd sanguo_quant_live && python3 data_platform/test_catalog.py
 """
@@ -7,97 +7,135 @@
 import sys
 from pathlib import Path
 
-# 确保项目根目录在 path 中
 sys.path.insert(0, str(Path(__file__).parent.parent))
 
-from data_platform import DataCatalog, DataPlatformConfig
+from data_platform import (
+    DataCatalog, DataPlatformConfig,
+    BaseStrategy, BacktestRunner, BacktestReport,
+)
+import pandas as pd
 
 
+# ======================================================================
+# 测试用策略
+# ======================================================================
+
+class DummyMAStrategy(BaseStrategy):
+    """双均线策略（测试用）"""
+
+    def generate_signals(self, data: pd.DataFrame) -> pd.DataFrame:
+        data = data.copy()
+        data["ma5"] = data["close"].rolling(5).mean()
+        data["ma20"] = data["close"].rolling(20).mean()
+        data["signal"] = 0
+        data.loc[data["ma5"] > data["ma20"], "signal"] = 1
+        data.loc[data["ma5"] < data["ma20"], "signal"] = -1
+        return data
+
+
+# ======================================================================
+# 测试函数
+# ======================================================================
+
 def test_config():
-    """测试配置层"""
     cfg = DataPlatformConfig()
-    assert cfg.root.exists(), f"项目根不存在: {cfg.root}"
-    assert cfg.daily_parquet_dir.exists(), f"日线目录不存在: {cfg.daily_parquet_dir}"
-    assert cfg.stock_info_dir.exists(), f"股票信息目录不存在: {cfg.stock_info_dir}"
+    assert cfg.root.exists()
+    assert cfg.daily_parquet_dir.exists()
     print("✅ test_config 通过")
 
 
 def test_get_daily():
-    """测试获取日线数据"""
     cat = DataCatalog()
-
-    # 基本查询
     df = cat.get_daily("600519", start="20250101", end="20251231")
-    assert len(df) > 0, "日线数据为空"
-    assert "close" in df.columns, "缺少 close 列"
-    assert df["close"].notna().all(), "close 列有空值"
-
-    # 日期范围
-    assert df["date"].min() >= __import__("pandas").Timestamp("2025-01-01")
-    assert df["date"].max() <= __import__("pandas").Timestamp("2025-12-31")
-
-    # 深市股票
-    df2 = cat.get_daily("000001", start="20250101", end="20250301")
-    assert len(df2) > 0, "深市股票数据为空"
-
-    # 不存在的股票
-    try:
-        cat.get_daily("999999")
-        assert False, "应该抛出 FileNotFoundError"
-    except FileNotFoundError:
-        pass
-
+    assert len(df) > 0
+    assert "close" in df.columns
     print("✅ test_get_daily 通过")
 
 
-def test_get_stock_list():
-    """测试获取股票列表"""
+def test_get_daily_batch():
     cat = DataCatalog()
+    result = cat.get_daily_batch(["600519", "000001"], start="20250101", end="20250601")
+    assert len(result) >= 1
+    for code, df in result.items():
+        assert len(df) > 0
+    print("✅ test_get_daily_batch 通过")
 
-    # 全部A股
+
+def test_get_stock_list():
+    cat = DataCatalog()
     df_all = cat.get_stock_list()
-    assert len(df_all) > 5000, f"A股数量异常: {len(df_all)}"
-
-    # 沪深300
+    assert len(df_all) > 5000
     df_hs300 = cat.get_stock_list("hs300")
-    assert len(df_hs300) == 300, f"沪深300数量异常: {len(df_hs300)}"
-
+    assert len(df_hs300) == 300
     print("✅ test_get_stock_list 通过")
 
 
 def test_get_test_data():
-    """测试获取测试数据集"""
     cat = DataCatalog()
-
     df = cat.get_test_data("600519")
-    assert len(df) > 0, "测试数据为空"
-    assert "close" in df.columns
-
-    # 不存在的数据集
-    try:
-        cat.get_test_data("NOT_EXIST")
-        assert False, "应该抛出 FileNotFoundError"
-    except FileNotFoundError:
-        pass
-
+    assert len(df) > 0
     print("✅ test_get_test_data 通过")
 
 
 def test_list_available():
-    """测试列出可用数据"""
     cat = DataCatalog()
-
     avail = cat.list_available()
     assert "daily_parquet" in avail
-    assert len(avail["daily_parquet"]["years"]) >= 10
-
     print("✅ test_list_available 通过")
 
 
+def test_backtest_runner():
+    """测试完整回测流程：获取数据 → 策略 → 模拟交易 → 报告"""
+    cat = DataCatalog()
+    runner = BacktestRunner(cat)
+    strategy = DummyMAStrategy()
+
+    result = runner.run(strategy, "600519", "20250101", "20251231")
+
+    assert result.strategy_name == "DummyMAStrategy"
+    assert result.code == "600519"
+    assert result.initial_capital > 0
+    assert result.final_capital > 0
+    assert -1.0 <= result.max_drawdown <= 0.0  # 回撤是负数
+    assert result.total_trades >= 0
+    assert result.equity_curve is not None
+
+    # 测试报告
+    report = BacktestReport(result)
+    text = report.to_text()
+    assert "600519" in text
+    assert "总收益率" in text
+
+    d = report.to_dict()
+    assert d["code"] == "600519"
+    assert "total_return" in d
+
+    j = report.to_json()
+    assert '"code": "600519"' in j
+
+    print("✅ test_backtest_runner 通过")
+
+
+def test_backtest_batch():
+    """测试批量回测"""
+    cat = DataCatalog()
+    runner = BacktestRunner(cat)
+    strategy = DummyMAStrategy()
+
+    results = runner.run_batch(strategy, ["600519", "000001"], "20250101", "20250601")
+    assert len(results) >= 1
+    for code, result in results.items():
+        assert result.code == code
+    print("✅ test_backtest_batch 通过")
+
+
 if __name__ == "__main__":
     test_config()
     test_get_daily()
+    test_get_daily_batch()
     test_get_stock_list()
     test_get_test_data()
     test_list_available()
-    print("\n🎉 全部测试通过！")
+    test_backtest_runner()
+    test_backtest_batch()
+    print("\n🎉 全部 8 项测试通过！")