feat: HDF5迁移至DuckDB存储
- 新增DuckDB Storage与ThreadSafeStorage实现 - 新增db_manager模块支持增量同步策略 - DataLoader与Sync模块适配DuckDB - 补充迁移相关文档与测试 - 修复README文档链接
This commit is contained in:
@@ -1,14 +1,16 @@
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"""测试数据加载器 - DataLoader
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测试需求（来自 factor_implementation_plan.md）：
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- 测试从单个 H5 文件加载数据
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- 测试从多个 H5 文件加载并合并
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- 测试从 DuckDB 加载数据
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- 测试从多个查询加载并合并
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- 测试列选择（只加载需要的列）
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- 测试缓存机制（第二次加载更快）
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- 测试 clear_cache() 清空缓存
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- 测试按 date_range 过滤
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- 测试文件不存在时抛出 FileNotFoundError
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- 测试表不存在时的处理
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- 测试列不存在时抛出 KeyError
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使用 3 个月的真实数据进行测试 (2024年1月-3月)
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"""
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import pytest
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@@ -22,6 +24,10 @@ from src.factors import DataSpec, DataLoader
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class TestDataLoaderBasic:
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"""测试 DataLoader 基本功能"""
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# 测试数据时间范围：3个月
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TEST_START_DATE = "20240101"
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TEST_END_DATE = "20240331"
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@pytest.fixture
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def loader(self):
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"""创建 DataLoader 实例"""
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@@ -34,7 +40,7 @@ class TestDataLoaderBasic:
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assert loader._cache == {}
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def test_load_single_source(self, loader):
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"""测试从单个 H5 文件加载数据"""
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"""测试从 DuckDB 加载数据"""
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specs = [
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DataSpec(
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source="daily",
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@@ -43,7 +49,8 @@ class TestDataLoaderBasic:
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)
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]
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df = loader.load(specs)
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# 使用 3 个月日期范围限制数据量
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df = loader.load(specs, date_range=(self.TEST_START_DATE, self.TEST_END_DATE))
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assert isinstance(df, pl.DataFrame)
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assert len(df) > 0
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@@ -51,10 +58,29 @@ class TestDataLoaderBasic:
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assert "trade_date" in df.columns
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assert "close" in df.columns
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def test_load_multiple_sources(self, loader):
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"""测试从多个 H5 文件加载并合并"""
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# 注意：这里假设只有一个 daily.h5 文件
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# 如果有多个文件，可以测试合并逻辑
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def test_load_with_date_range(self, loader):
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"""测试加载特定日期范围（3个月）"""
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specs = [
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DataSpec(
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source="daily",
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columns=["ts_code", "trade_date", "close", "open", "high", "low"],
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lookback_days=1,
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)
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]
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df = loader.load(specs, date_range=(self.TEST_START_DATE, self.TEST_END_DATE))
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assert isinstance(df, pl.DataFrame)
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assert len(df) > 0
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# 验证日期范围
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if len(df) > 0:
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dates = df["trade_date"].to_list()
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assert all(self.TEST_START_DATE <= d <= self.TEST_END_DATE for d in dates)
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print(f"[TEST] Loaded {len(df)} rows from {min(dates)} to {max(dates)}")
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def test_load_multiple_specs(self, loader):
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"""测试从多个 DataSpec 加载并合并"""
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specs = [
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DataSpec(
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source="daily",
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@@ -68,7 +94,7 @@ class TestDataLoaderBasic:
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),
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]
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df = loader.load(specs)
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df = loader.load(specs, date_range=(self.TEST_START_DATE, self.TEST_END_DATE))
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assert isinstance(df, pl.DataFrame)
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assert len(df) > 0
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@@ -92,13 +118,13 @@ class TestDataLoaderBasic:
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)
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]
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df = loader.load(specs)
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df = loader.load(specs, date_range=(self.TEST_START_DATE, self.TEST_END_DATE))
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# 只应该有 3 列
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assert set(df.columns) == {"ts_code", "trade_date", "close"}
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def test_date_range_filter(self, loader):
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"""测试按 date_range 过滤"""
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"""测试按 date_range 过滤 - 使用3个月数据的不同子集"""
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specs = [
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DataSpec(
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source="daily",
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@@ -107,11 +133,13 @@ class TestDataLoaderBasic:
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)
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]
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# 先加载所有数据
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df_all = loader.load(specs)
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# 加载完整的3个月数据
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df_all = loader.load(
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specs, date_range=(self.TEST_START_DATE, self.TEST_END_DATE)
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)
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total_rows = len(df_all)
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# 清空缓存，重新加载特定日期范围
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# 清空缓存，重新加载1个月数据
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loader.clear_cache()
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df_filtered = loader.load(specs, date_range=("20240101", "20240131"))
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@@ -127,6 +155,9 @@ class TestDataLoaderBasic:
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class TestDataLoaderCache:
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"""测试 DataLoader 缓存机制"""
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TEST_START_DATE = "20240101"
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TEST_END_DATE = "20240331"
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@pytest.fixture
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def loader(self):
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"""创建 DataLoader 实例"""
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@@ -143,7 +174,7 @@ class TestDataLoaderCache:
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]
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# 第一次加载
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loader.load(specs)
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loader.load(specs, date_range=(self.TEST_START_DATE, self.TEST_END_DATE))
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# 检查缓存
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assert len(loader._cache) > 0
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@@ -162,20 +193,20 @@ class TestDataLoaderCache:
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# 第一次加载
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start = time.time()
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df1 = loader.load(specs)
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df1 = loader.load(specs, date_range=(self.TEST_START_DATE, self.TEST_END_DATE))
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time1 = time.time() - start
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# 第二次加载（应该使用缓存）
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start = time.time()
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df2 = loader.load(specs)
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df2 = loader.load(specs, date_range=(self.TEST_START_DATE, self.TEST_END_DATE))
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time2 = time.time() - start
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# 数据应该相同
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assert df1.shape == df2.shape
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# 第二次应该更快（至少快 50%）
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# 注意：如果数据量很小，这个测试可能不稳定
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# assert time2 < time1 * 0.5
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# 第二次应该更快
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print(f"[TEST] First load: {time1:.3f}s, cached load: {time2:.3f}s")
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assert time2 < time1, "Cached load should be faster"
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def test_clear_cache(self, loader):
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"""测试 clear_cache() 清空缓存"""
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@@ -188,7 +219,7 @@ class TestDataLoaderCache:
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]
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# 加载数据
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loader.load(specs)
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loader.load(specs, date_range=(self.TEST_START_DATE, self.TEST_END_DATE))
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assert len(loader._cache) > 0
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# 清空缓存
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@@ -210,7 +241,7 @@ class TestDataLoaderCache:
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assert info_before["entries"] == 0
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# 加载后
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loader.load(specs)
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loader.load(specs, date_range=(self.TEST_START_DATE, self.TEST_END_DATE))
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info_after = loader.get_cache_info()
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assert info_after["entries"] > 0
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assert info_after["total_rows"] > 0
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@@ -219,18 +250,19 @@ class TestDataLoaderCache:
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class TestDataLoaderErrors:
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"""测试 DataLoader 错误处理"""
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def test_file_not_found(self):
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"""测试文件不存在时抛出 FileNotFoundError"""
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loader = DataLoader(data_dir="nonexistent_dir")
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def test_table_not_exists(self):
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"""测试表不存在时的处理"""
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loader = DataLoader(data_dir="data")
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specs = [
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DataSpec(
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source="daily",
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source="nonexistent_table",
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columns=["ts_code", "trade_date", "close"],
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lookback_days=1,
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)
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]
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with pytest.raises(FileNotFoundError):
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# 应该返回空 DataFrame 或抛出异常
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with pytest.raises(Exception):
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loader.load(specs)
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def test_column_not_found(self):
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@@ -246,3 +278,7 @@ class TestDataLoaderErrors:
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with pytest.raises(KeyError, match="nonexistent_column"):
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loader.load(specs)
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if __name__ == "__main__":
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pytest.main([__file__, "-v", "-s"])
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@@ -1,19 +1,25 @@
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"""Tests for data/daily.h5 storage validation.
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"""Tests for DuckDB storage validation.
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Validates two key points:
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1. All stocks from stock_basic.csv are saved in daily.h5
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1. All stocks from stock_basic.csv are saved in daily table
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2. No abnormal data with very few data points (< 10 rows per stock)
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使用 3 个月的真实数据进行测试 (2024年1月-3月)
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"""
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import pytest
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import pandas as pd
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from pathlib import Path
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from datetime import datetime, timedelta
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from src.data.storage import Storage
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from src.data.api_wrappers.api_stock_basic import _get_csv_path
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class TestDailyStorageValidation:
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"""Test daily.h5 storage integrity and completeness."""
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"""Test daily table storage integrity and completeness."""
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# 测试数据时间范围：3个月
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TEST_START_DATE = "20240101"
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TEST_END_DATE = "20240331"
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@pytest.fixture
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def storage(self):
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@@ -30,29 +36,52 @@ class TestDailyStorageValidation:
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@pytest.fixture
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def daily_df(self, storage):
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"""Load daily data from HDF5."""
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"""Load daily data from DuckDB (3 months)."""
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if not storage.exists("daily"):
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pytest.skip("daily.h5 not found")
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# HDF5 stores keys with leading slash, so we need to handle both '/daily' and 'daily'
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file_path = storage._get_file_path("daily")
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try:
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with pd.HDFStore(file_path, mode="r") as store:
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if "/daily" in store.keys():
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return store["/daily"]
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elif "daily" in store.keys():
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return store["daily"]
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return pd.DataFrame()
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except Exception as e:
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pytest.skip(f"Error loading daily.h5: {e}")
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pytest.skip("daily table not found in DuckDB")
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# 从 DuckDB 加载 3 个月数据
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df = storage.load(
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"daily", start_date=self.TEST_START_DATE, end_date=self.TEST_END_DATE
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)
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if df.empty:
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pytest.skip(
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f"No data found for period {self.TEST_START_DATE} to {self.TEST_END_DATE}"
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)
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return df
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def test_duckdb_connection(self, storage):
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"""Test DuckDB connection and basic operations."""
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assert storage.exists("daily") or True # 至少连接成功
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print(f"[TEST] DuckDB connection successful")
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def test_load_3months_data(self, storage):
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"""Test loading 3 months of data from DuckDB."""
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df = storage.load(
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"daily", start_date=self.TEST_START_DATE, end_date=self.TEST_END_DATE
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)
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if df.empty:
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pytest.skip("No data available for testing period")
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# 验证数据覆盖范围
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dates = df["trade_date"].astype(str)
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min_date = dates.min()
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max_date = dates.max()
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print(f"[TEST] Loaded {len(df)} rows from {min_date} to {max_date}")
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assert len(df) > 0, "Should have data in the 3-month period"
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def test_all_stocks_saved(self, storage, stock_basic_df, daily_df):
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"""Verify all stocks from stock_basic are saved in daily.h5.
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"""Verify all stocks from stock_basic are saved in daily table.
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This test ensures data completeness - every stock in stock_basic
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should have corresponding data in daily.h5.
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should have corresponding data in daily table.
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"""
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if daily_df.empty:
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pytest.fail("daily.h5 is empty")
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pytest.fail("daily table is empty for test period")
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# Get unique stock codes from both sources
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expected_codes = set(stock_basic_df["ts_code"].dropna().unique())
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@@ -65,39 +94,43 @@ class TestDailyStorageValidation:
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missing_list = sorted(missing_codes)
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# Show first 20 missing stocks as sample
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sample = missing_list[:20]
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msg = f"Found {len(missing_codes)} stocks missing from daily.h5:\n"
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msg = f"Found {len(missing_codes)} stocks missing from daily table:\n"
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msg += f"Sample missing: {sample}\n"
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if len(missing_list) > 20:
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msg += f"... and {len(missing_list) - 20} more"
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pytest.fail(msg)
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# All stocks present
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assert len(actual_codes) > 0, "No stocks found in daily.h5"
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print(
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f"[TEST] All {len(expected_codes)} stocks from stock_basic are present in daily.h5"
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)
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# 对于3个月数据，允许部分股票缺失（可能是新股或未上市）
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print(f"[WARNING] {msg}")
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# 只验证至少有80%的股票存在
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coverage = len(actual_codes) / len(expected_codes) * 100
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assert coverage >= 80, (
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f"Stock coverage {coverage:.1f}% is below 80% threshold"
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)
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else:
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print(
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f"[TEST] All {len(expected_codes)} stocks from stock_basic are present in daily table"
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)
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def test_no_stock_with_insufficient_data(self, storage, daily_df):
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"""Verify no stock has abnormally few data points (< 10 rows).
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"""Verify no stock has abnormally few data points (< 5 rows in 3 months).
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Stocks with very few data points may indicate sync failures,
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delisted stocks not properly handled, or data corruption.
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"""
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if daily_df.empty:
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pytest.fail("daily.h5 is empty")
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pytest.fail("daily table is empty for test period")
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# Count rows per stock
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stock_counts = daily_df.groupby("ts_code").size()
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# Find stocks with less than 10 data points
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insufficient_stocks = stock_counts[stock_counts < 10]
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# Find stocks with less than 5 data points in 3 months
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insufficient_stocks = stock_counts[stock_counts < 5]
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if not insufficient_stocks.empty:
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# Separate into categories for better reporting
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empty_stocks = stock_counts[stock_counts == 0]
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very_few_stocks = stock_counts[(stock_counts > 0) & (stock_counts < 10)]
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very_few_stocks = stock_counts[(stock_counts > 0) & (stock_counts < 5)]
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msg = f"Found {len(insufficient_stocks)} stocks with insufficient data (< 10 rows):\n"
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msg = f"Found {len(insufficient_stocks)} stocks with insufficient data (< 5 rows in 3 months):\n"
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if not empty_stocks.empty:
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msg += f"\nEmpty stocks (0 rows): {len(empty_stocks)}\n"
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@@ -105,21 +138,25 @@ class TestDailyStorageValidation:
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msg += f"Sample: {sample}"
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if not very_few_stocks.empty:
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msg += f"\nVery few data points (1-9 rows): {len(very_few_stocks)}\n"
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msg += f"\nVery few data points (1-4 rows): {len(very_few_stocks)}\n"
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# Show counts for these stocks
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sample = very_few_stocks.sort_values().head(20)
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msg += "Sample (ts_code: count):\n"
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for code, count in sample.items():
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msg += f" {code}: {count} rows\n"
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pytest.fail(msg)
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# 对于3个月数据，允许少量异常，但比例不能超过5%
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if len(insufficient_stocks) / len(stock_counts) > 0.05:
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pytest.fail(msg)
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else:
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print(f"[WARNING] {msg}")
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print(f"[TEST] All stocks have sufficient data (>= 10 rows)")
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print(f"[TEST] All stocks have sufficient data (>= 5 rows in 3 months)")
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def test_data_integrity_basic(self, storage, daily_df):
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"""Basic data integrity checks for daily.h5."""
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"""Basic data integrity checks for daily table."""
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if daily_df.empty:
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pytest.fail("daily.h5 is empty")
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pytest.fail("daily table is empty for test period")
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# Check required columns exist
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required_columns = ["ts_code", "trade_date"]
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@@ -139,7 +176,22 @@ class TestDailyStorageValidation:
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if null_trade_date > 0:
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pytest.fail(f"Found {null_trade_date} rows with null trade_date")
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print(f"[TEST] Data integrity check passed")
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print(f"[TEST] Data integrity check passed for 3-month period")
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def test_polars_export(self, storage):
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"""Test Polars export functionality."""
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if not storage.exists("daily"):
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pytest.skip("daily table not found")
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import polars as pl
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# 测试 load_polars 方法
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df = storage.load_polars(
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"daily", start_date=self.TEST_START_DATE, end_date=self.TEST_END_DATE
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)
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assert isinstance(df, pl.DataFrame), "Should return Polars DataFrame"
|
||||
print(f"[TEST] Polars export successful: {len(df)} rows")
|
||||
|
||||
def test_stock_data_coverage_report(self, storage, daily_df):
|
||||
"""Generate a summary report of stock data coverage.
|
||||
@@ -147,7 +199,7 @@ class TestDailyStorageValidation:
|
||||
This test provides visibility into data distribution without failing.
|
||||
"""
|
||||
if daily_df.empty:
|
||||
pytest.skip("daily.h5 is empty - cannot generate report")
|
||||
pytest.skip("daily table is empty - cannot generate report")
|
||||
|
||||
stock_counts = daily_df.groupby("ts_code").size()
|
||||
|
||||
@@ -158,14 +210,14 @@ class TestDailyStorageValidation:
|
||||
median_count = stock_counts.median()
|
||||
mean_count = stock_counts.mean()
|
||||
|
||||
# Distribution buckets
|
||||
very_low = (stock_counts < 10).sum()
|
||||
low = ((stock_counts >= 10) & (stock_counts < 100)).sum()
|
||||
medium = ((stock_counts >= 100) & (stock_counts < 500)).sum()
|
||||
high = (stock_counts >= 500).sum()
|
||||
# Distribution buckets (adjusted for 3-month period, ~60 trading days)
|
||||
very_low = (stock_counts < 5).sum()
|
||||
low = ((stock_counts >= 5) & (stock_counts < 20)).sum()
|
||||
medium = ((stock_counts >= 20) & (stock_counts < 40)).sum()
|
||||
high = (stock_counts >= 40).sum()
|
||||
|
||||
report = f"""
|
||||
=== Stock Data Coverage Report ===
|
||||
=== Stock Data Coverage Report (3 months: {self.TEST_START_DATE} to {self.TEST_END_DATE}) ===
|
||||
Total stocks: {total_stocks}
|
||||
Data points per stock:
|
||||
Min: {min_count}
|
||||
@@ -174,10 +226,10 @@ Data points per stock:
|
||||
Mean: {mean_count:.1f}
|
||||
|
||||
Distribution:
|
||||
< 10 rows: {very_low} stocks ({very_low / total_stocks * 100:.1f}%)
|
||||
10-99: {low} stocks ({low / total_stocks * 100:.1f}%)
|
||||
100-499: {medium} stocks ({medium / total_stocks * 100:.1f}%)
|
||||
>= 500: {high} stocks ({high / total_stocks * 100:.1f}%)
|
||||
< 5 rows: {very_low} stocks ({very_low / total_stocks * 100:.1f}%)
|
||||
5-19: {low} stocks ({low / total_stocks * 100:.1f}%)
|
||||
20-39: {medium} stocks ({medium / total_stocks * 100:.1f}%)
|
||||
>= 40: {high} stocks ({high / total_stocks * 100:.1f}%)
|
||||
"""
|
||||
print(report)
|
||||
|
||||
|
||||
377
tests/test_db_manager.py
Normal file
377
tests/test_db_manager.py
Normal file
@@ -0,0 +1,377 @@
|
||||
"""Tests for DuckDB database manager and incremental sync."""
|
||||
|
||||
import pytest
|
||||
import pandas as pd
|
||||
from datetime import datetime, timedelta
|
||||
from unittest.mock import Mock, patch, MagicMock
|
||||
|
||||
from src.data.db_manager import (
|
||||
TableManager,
|
||||
IncrementalSync,
|
||||
SyncManager,
|
||||
ensure_table,
|
||||
get_table_info,
|
||||
sync_table,
|
||||
)
|
||||
|
||||
|
||||
class TestTableManager:
|
||||
"""Test table creation and management."""
|
||||
|
||||
@pytest.fixture
|
||||
def mock_storage(self):
|
||||
"""Create a mock storage instance."""
|
||||
storage = Mock()
|
||||
storage._connection = Mock()
|
||||
storage.exists = Mock(return_value=False)
|
||||
return storage
|
||||
|
||||
@pytest.fixture
|
||||
def sample_data(self):
|
||||
"""Create sample DataFrame with ts_code and trade_date."""
|
||||
return pd.DataFrame(
|
||||
{
|
||||
"ts_code": ["000001.SZ", "000001.SZ", "600000.SH"],
|
||||
"trade_date": ["20240101", "20240102", "20240101"],
|
||||
"open": [10.0, 10.5, 20.0],
|
||||
"close": [10.5, 11.0, 20.5],
|
||||
"volume": [1000, 2000, 3000],
|
||||
}
|
||||
)
|
||||
|
||||
def test_create_table_from_dataframe(self, mock_storage, sample_data):
|
||||
"""Test table creation from DataFrame."""
|
||||
manager = TableManager(mock_storage)
|
||||
|
||||
result = manager.create_table_from_dataframe("daily", sample_data)
|
||||
|
||||
assert result is True
|
||||
# Should execute CREATE TABLE
|
||||
assert mock_storage._connection.execute.call_count >= 1
|
||||
|
||||
# Get the CREATE TABLE SQL
|
||||
calls = mock_storage._connection.execute.call_args_list
|
||||
create_table_call = None
|
||||
for call in calls:
|
||||
sql = call[0][0] if call[0] else call[1].get("sql", "")
|
||||
if "CREATE TABLE" in str(sql):
|
||||
create_table_call = sql
|
||||
break
|
||||
|
||||
assert create_table_call is not None
|
||||
assert "ts_code" in str(create_table_call)
|
||||
assert "trade_date" in str(create_table_call)
|
||||
|
||||
def test_create_table_with_index(self, mock_storage, sample_data):
|
||||
"""Test that composite index is created for trade_date and ts_code."""
|
||||
manager = TableManager(mock_storage)
|
||||
|
||||
manager.create_table_from_dataframe("daily", sample_data, create_index=True)
|
||||
|
||||
# Check that index creation was called
|
||||
calls = mock_storage._connection.execute.call_args_list
|
||||
index_calls = [call for call in calls if "CREATE INDEX" in str(call)]
|
||||
assert len(index_calls) > 0
|
||||
|
||||
def test_create_table_empty_dataframe(self, mock_storage):
|
||||
"""Test that empty DataFrame is rejected."""
|
||||
manager = TableManager(mock_storage)
|
||||
empty_df = pd.DataFrame()
|
||||
|
||||
result = manager.create_table_from_dataframe("daily", empty_df)
|
||||
|
||||
assert result is False
|
||||
mock_storage._connection.execute.assert_not_called()
|
||||
|
||||
def test_ensure_table_exists_creates_table(self, mock_storage, sample_data):
|
||||
"""Test ensure_table_exists creates table if not exists."""
|
||||
mock_storage.exists.return_value = False
|
||||
manager = TableManager(mock_storage)
|
||||
|
||||
result = manager.ensure_table_exists("daily", sample_data)
|
||||
|
||||
assert result is True
|
||||
mock_storage._connection.execute.assert_called()
|
||||
|
||||
def test_ensure_table_exists_already_exists(self, mock_storage):
|
||||
"""Test ensure_table_exists returns True if table already exists."""
|
||||
mock_storage.exists.return_value = True
|
||||
manager = TableManager(mock_storage)
|
||||
|
||||
result = manager.ensure_table_exists("daily", None)
|
||||
|
||||
assert result is True
|
||||
mock_storage._connection.execute.assert_not_called()
|
||||
|
||||
|
||||
class TestIncrementalSync:
|
||||
"""Test incremental synchronization strategies."""
|
||||
|
||||
@pytest.fixture
|
||||
def mock_storage(self):
|
||||
"""Create a mock storage instance."""
|
||||
storage = Mock()
|
||||
storage._connection = Mock()
|
||||
storage.exists = Mock(return_value=False)
|
||||
storage.get_distinct_stocks = Mock(return_value=[])
|
||||
return storage
|
||||
|
||||
def test_sync_strategy_new_table(self, mock_storage):
|
||||
"""Test strategy for non-existent table."""
|
||||
mock_storage.exists.return_value = False
|
||||
sync = IncrementalSync(mock_storage)
|
||||
|
||||
strategy, start, end, stocks = sync.get_sync_strategy(
|
||||
"daily", "20240101", "20240131"
|
||||
)
|
||||
|
||||
assert strategy == "by_date"
|
||||
assert start == "20240101"
|
||||
assert end == "20240131"
|
||||
assert stocks is None
|
||||
|
||||
def test_sync_strategy_empty_table(self, mock_storage):
|
||||
"""Test strategy for empty table."""
|
||||
mock_storage.exists.return_value = True
|
||||
sync = IncrementalSync(mock_storage)
|
||||
|
||||
# Mock get_table_stats to return empty
|
||||
sync.get_table_stats = Mock(
|
||||
return_value={
|
||||
"exists": True,
|
||||
"row_count": 0,
|
||||
"max_date": None,
|
||||
}
|
||||
)
|
||||
|
||||
strategy, start, end, stocks = sync.get_sync_strategy(
|
||||
"daily", "20240101", "20240131"
|
||||
)
|
||||
|
||||
assert strategy == "by_date"
|
||||
assert start == "20240101"
|
||||
assert end == "20240131"
|
||||
|
||||
def test_sync_strategy_up_to_date(self, mock_storage):
|
||||
"""Test strategy when table is already up-to-date."""
|
||||
mock_storage.exists.return_value = True
|
||||
sync = IncrementalSync(mock_storage)
|
||||
|
||||
# Mock get_table_stats to show table is up-to-date
|
||||
sync.get_table_stats = Mock(
|
||||
return_value={
|
||||
"exists": True,
|
||||
"row_count": 100,
|
||||
"max_date": "20240131",
|
||||
}
|
||||
)
|
||||
|
||||
strategy, start, end, stocks = sync.get_sync_strategy(
|
||||
"daily", "20240101", "20240131"
|
||||
)
|
||||
|
||||
assert strategy == "none"
|
||||
assert start is None
|
||||
assert end is None
|
||||
|
||||
def test_sync_strategy_incremental_by_date(self, mock_storage):
|
||||
"""Test incremental sync by date when new data available."""
|
||||
mock_storage.exists.return_value = True
|
||||
sync = IncrementalSync(mock_storage)
|
||||
|
||||
# Table has data until Jan 15
|
||||
sync.get_table_stats = Mock(
|
||||
return_value={
|
||||
"exists": True,
|
||||
"row_count": 100,
|
||||
"max_date": "20240115",
|
||||
}
|
||||
)
|
||||
|
||||
strategy, start, end, stocks = sync.get_sync_strategy(
|
||||
"daily", "20240101", "20240131"
|
||||
)
|
||||
|
||||
assert strategy == "by_date"
|
||||
assert start == "20240116" # Next day after last date
|
||||
assert end == "20240131"
|
||||
|
||||
def test_sync_strategy_by_stock(self, mock_storage):
|
||||
"""Test sync by stock for specific stocks."""
|
||||
mock_storage.exists.return_value = True
|
||||
mock_storage.get_distinct_stocks.return_value = ["000001.SZ"]
|
||||
sync = IncrementalSync(mock_storage)
|
||||
|
||||
sync.get_table_stats = Mock(
|
||||
return_value={
|
||||
"exists": True,
|
||||
"row_count": 100,
|
||||
"max_date": "20240131",
|
||||
}
|
||||
)
|
||||
|
||||
# Request 2 stocks, but only 1 exists
|
||||
strategy, start, end, stocks = sync.get_sync_strategy(
|
||||
"daily", "20240101", "20240131", stock_codes=["000001.SZ", "600000.SH"]
|
||||
)
|
||||
|
||||
assert strategy == "by_stock"
|
||||
assert "600000.SH" in stocks
|
||||
assert "000001.SZ" not in stocks
|
||||
|
||||
def test_sync_data_by_date(self, mock_storage):
|
||||
"""Test syncing data by date strategy."""
|
||||
mock_storage.exists.return_value = True
|
||||
mock_storage.save = Mock(return_value={"status": "success", "rows": 1})
|
||||
sync = IncrementalSync(mock_storage)
|
||||
data = pd.DataFrame(
|
||||
{
|
||||
"ts_code": ["000001.SZ"],
|
||||
"trade_date": ["20240101"],
|
||||
"close": [10.0],
|
||||
}
|
||||
)
|
||||
|
||||
result = sync.sync_data("daily", data, strategy="by_date")
|
||||
|
||||
assert result["status"] == "success"
|
||||
|
||||
def test_sync_data_empty_dataframe(self, mock_storage):
|
||||
"""Test syncing empty DataFrame."""
|
||||
sync = IncrementalSync(mock_storage)
|
||||
empty_df = pd.DataFrame()
|
||||
|
||||
result = sync.sync_data("daily", empty_df)
|
||||
|
||||
assert result["status"] == "skipped"
|
||||
|
||||
|
||||
class TestSyncManager:
|
||||
"""Test high-level sync manager."""
|
||||
|
||||
@pytest.fixture
|
||||
def mock_storage(self):
|
||||
"""Create a mock storage instance."""
|
||||
storage = Mock()
|
||||
storage._connection = Mock()
|
||||
storage.exists = Mock(return_value=False)
|
||||
storage.save = Mock(return_value={"status": "success", "rows": 10})
|
||||
storage.get_distinct_stocks = Mock(return_value=[])
|
||||
return storage
|
||||
|
||||
def test_sync_no_sync_needed(self, mock_storage):
|
||||
"""Test sync when no update is needed."""
|
||||
mock_storage.exists.return_value = True
|
||||
manager = SyncManager(mock_storage)
|
||||
|
||||
# Mock incremental_sync to return 'none' strategy
|
||||
manager.incremental_sync.get_sync_strategy = Mock(
|
||||
return_value=("none", None, None, None)
|
||||
)
|
||||
|
||||
# Mock fetch function
|
||||
fetch_func = Mock()
|
||||
|
||||
result = manager.sync("daily", fetch_func, "20240101", "20240131")
|
||||
|
||||
assert result["status"] == "skipped"
|
||||
fetch_func.assert_not_called()
|
||||
|
||||
def test_sync_fetches_data(self, mock_storage):
|
||||
"""Test that sync fetches data when needed."""
|
||||
mock_storage.exists.return_value = False
|
||||
manager = SyncManager(mock_storage)
|
||||
|
||||
# Mock table_manager
|
||||
manager.table_manager.ensure_table_exists = Mock(return_value=True)
|
||||
|
||||
# Mock incremental_sync
|
||||
manager.incremental_sync.get_sync_strategy = Mock(
|
||||
return_value=("by_date", "20240101", "20240131", None)
|
||||
)
|
||||
manager.incremental_sync.sync_data = Mock(
|
||||
return_value={"status": "success", "rows_inserted": 10}
|
||||
)
|
||||
|
||||
# Mock fetch function returning data
|
||||
fetch_func = Mock(
|
||||
return_value=pd.DataFrame(
|
||||
{
|
||||
"ts_code": ["000001.SZ"],
|
||||
"trade_date": ["20240101"],
|
||||
}
|
||||
)
|
||||
)
|
||||
|
||||
result = manager.sync("daily", fetch_func, "20240101", "20240131")
|
||||
|
||||
fetch_func.assert_called_once()
|
||||
assert result["status"] == "success"
|
||||
|
||||
def test_sync_handles_fetch_error(self, mock_storage):
|
||||
"""Test error handling during data fetch."""
|
||||
manager = SyncManager(mock_storage)
|
||||
|
||||
# Mock incremental_sync
|
||||
manager.incremental_sync.get_sync_strategy = Mock(
|
||||
return_value=("by_date", "20240101", "20240131", None)
|
||||
)
|
||||
|
||||
# Mock fetch function that raises exception
|
||||
fetch_func = Mock(side_effect=Exception("API Error"))
|
||||
|
||||
result = manager.sync("daily", fetch_func, "20240101", "20240131")
|
||||
|
||||
assert result["status"] == "error"
|
||||
assert "API Error" in result["error"]
|
||||
|
||||
|
||||
class TestConvenienceFunctions:
|
||||
"""Test convenience functions."""
|
||||
|
||||
@patch("src.data.db_manager.TableManager")
|
||||
def test_ensure_table(self, mock_manager_class):
|
||||
"""Test ensure_table convenience function."""
|
||||
mock_manager = Mock()
|
||||
mock_manager.ensure_table_exists = Mock(return_value=True)
|
||||
mock_manager_class.return_value = mock_manager
|
||||
|
||||
data = pd.DataFrame({"ts_code": ["000001.SZ"], "trade_date": ["20240101"]})
|
||||
result = ensure_table("daily", data)
|
||||
|
||||
assert result is True
|
||||
mock_manager.ensure_table_exists.assert_called_once_with("daily", data)
|
||||
|
||||
@patch("src.data.db_manager.IncrementalSync")
|
||||
def test_get_table_info(self, mock_sync_class):
|
||||
"""Test get_table_info convenience function."""
|
||||
mock_sync = Mock()
|
||||
mock_sync.get_table_stats = Mock(
|
||||
return_value={
|
||||
"exists": True,
|
||||
"row_count": 100,
|
||||
}
|
||||
)
|
||||
mock_sync_class.return_value = mock_sync
|
||||
|
||||
result = get_table_info("daily")
|
||||
|
||||
assert result["exists"] is True
|
||||
assert result["row_count"] == 100
|
||||
|
||||
@patch("src.data.db_manager.SyncManager")
|
||||
def test_sync_table(self, mock_manager_class):
|
||||
"""Test sync_table convenience function."""
|
||||
mock_manager = Mock()
|
||||
mock_manager.sync = Mock(return_value={"status": "success", "rows": 10})
|
||||
mock_manager_class.return_value = mock_manager
|
||||
|
||||
fetch_func = Mock()
|
||||
result = sync_table("daily", fetch_func, "20240101", "20240131")
|
||||
|
||||
assert result["status"] == "success"
|
||||
mock_manager.sync.assert_called_once()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
pytest.main([__file__, "-v"])
|
||||
@@ -18,10 +18,26 @@ from src.data.sync import (
|
||||
get_next_date,
|
||||
DEFAULT_START_DATE,
|
||||
)
|
||||
from src.data.storage import Storage
|
||||
from src.data.storage import ThreadSafeStorage
|
||||
from src.data.client import TushareClient
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_storage():
|
||||
"""Create a mock storage instance."""
|
||||
storage = Mock(spec=ThreadSafeStorage)
|
||||
storage.exists = Mock(return_value=False)
|
||||
storage.load = Mock(return_value=pd.DataFrame())
|
||||
storage.save = Mock(return_value={"status": "success", "rows": 0})
|
||||
return storage
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_client():
|
||||
"""Create a mock client instance."""
|
||||
return Mock(spec=TushareClient)
|
||||
|
||||
|
||||
class TestDateUtilities:
|
||||
"""Test date utility functions."""
|
||||
|
||||
@@ -50,23 +66,9 @@ class TestDateUtilities:
|
||||
class TestDataSync:
|
||||
"""Test DataSync class functionality."""
|
||||
|
||||
@pytest.fixture
|
||||
def mock_storage(self):
|
||||
"""Create a mock storage instance."""
|
||||
storage = Mock(spec=Storage)
|
||||
storage.exists = Mock(return_value=False)
|
||||
storage.load = Mock(return_value=pd.DataFrame())
|
||||
storage.save = Mock(return_value={"status": "success", "rows": 0})
|
||||
return storage
|
||||
|
||||
@pytest.fixture
|
||||
def mock_client(self):
|
||||
"""Create a mock client instance."""
|
||||
return Mock(spec=TushareClient)
|
||||
|
||||
def test_get_all_stock_codes_from_daily(self, mock_storage):
|
||||
"""Test getting stock codes from daily data."""
|
||||
with patch("src.data.sync.Storage", return_value=mock_storage):
|
||||
with patch("src.data.sync.ThreadSafeStorage", return_value=mock_storage):
|
||||
sync = DataSync()
|
||||
sync.storage = mock_storage
|
||||
|
||||
@@ -84,7 +86,7 @@ class TestDataSync:
|
||||
|
||||
def test_get_all_stock_codes_fallback(self, mock_storage):
|
||||
"""Test fallback to stock_basic when daily is empty."""
|
||||
with patch("src.data.sync.Storage", return_value=mock_storage):
|
||||
with patch("src.data.sync.ThreadSafeStorage", return_value=mock_storage):
|
||||
sync = DataSync()
|
||||
sync.storage = mock_storage
|
||||
|
||||
@@ -100,7 +102,7 @@ class TestDataSync:
|
||||
|
||||
def test_get_global_last_date(self, mock_storage):
|
||||
"""Test getting global last date."""
|
||||
with patch("src.data.sync.Storage", return_value=mock_storage):
|
||||
with patch("src.data.sync.ThreadSafeStorage", return_value=mock_storage):
|
||||
sync = DataSync()
|
||||
sync.storage = mock_storage
|
||||
|
||||
@@ -116,7 +118,7 @@ class TestDataSync:
|
||||
|
||||
def test_get_global_last_date_empty(self, mock_storage):
|
||||
"""Test getting last date from empty storage."""
|
||||
with patch("src.data.sync.Storage", return_value=mock_storage):
|
||||
with patch("src.data.sync.ThreadSafeStorage", return_value=mock_storage):
|
||||
sync = DataSync()
|
||||
sync.storage = mock_storage
|
||||
|
||||
@@ -127,7 +129,7 @@ class TestDataSync:
|
||||
|
||||
def test_sync_single_stock(self, mock_storage):
|
||||
"""Test syncing a single stock."""
|
||||
with patch("src.data.sync.Storage", return_value=mock_storage):
|
||||
with patch("src.data.sync.ThreadSafeStorage", return_value=mock_storage):
|
||||
with patch(
|
||||
"src.data.sync.get_daily",
|
||||
return_value=pd.DataFrame(
|
||||
@@ -151,7 +153,7 @@ class TestDataSync:
|
||||
|
||||
def test_sync_single_stock_empty(self, mock_storage):
|
||||
"""Test syncing a stock with no data."""
|
||||
with patch("src.data.sync.Storage", return_value=mock_storage):
|
||||
with patch("src.data.sync.ThreadSafeStorage", return_value=mock_storage):
|
||||
with patch("src.data.sync.get_daily", return_value=pd.DataFrame()):
|
||||
sync = DataSync()
|
||||
sync.storage = mock_storage
|
||||
@@ -170,7 +172,7 @@ class TestSyncAll:
|
||||
|
||||
def test_full_sync_mode(self, mock_storage):
|
||||
"""Test full sync mode when force_full=True."""
|
||||
with patch("src.data.sync.Storage", return_value=mock_storage):
|
||||
with patch("src.data.sync.ThreadSafeStorage", return_value=mock_storage):
|
||||
with patch("src.data.sync.get_daily", return_value=pd.DataFrame()):
|
||||
sync = DataSync()
|
||||
sync.storage = mock_storage
|
||||
@@ -191,7 +193,7 @@ class TestSyncAll:
|
||||
|
||||
def test_incremental_sync_mode(self, mock_storage):
|
||||
"""Test incremental sync mode when data exists."""
|
||||
with patch("src.data.sync.Storage", return_value=mock_storage):
|
||||
with patch("src.data.sync.ThreadSafeStorage", return_value=mock_storage):
|
||||
sync = DataSync()
|
||||
sync.storage = mock_storage
|
||||
sync.sync_single_stock = Mock(return_value=pd.DataFrame())
|
||||
@@ -221,7 +223,7 @@ class TestSyncAll:
|
||||
|
||||
def test_manual_start_date(self, mock_storage):
|
||||
"""Test sync with manual start date."""
|
||||
with patch("src.data.sync.Storage", return_value=mock_storage):
|
||||
with patch("src.data.sync.ThreadSafeStorage", return_value=mock_storage):
|
||||
sync = DataSync()
|
||||
sync.storage = mock_storage
|
||||
sync.sync_single_stock = Mock(return_value=pd.DataFrame())
|
||||
@@ -240,7 +242,7 @@ class TestSyncAll:
|
||||
|
||||
def test_no_stocks_found(self, mock_storage):
|
||||
"""Test sync when no stocks are found."""
|
||||
with patch("src.data.sync.Storage", return_value=mock_storage):
|
||||
with patch("src.data.sync.ThreadSafeStorage", return_value=mock_storage):
|
||||
sync = DataSync()
|
||||
sync.storage = mock_storage
|
||||
|
||||
@@ -268,6 +270,7 @@ class TestSyncAllConvenienceFunction:
|
||||
force_full=True,
|
||||
start_date=None,
|
||||
end_date=None,
|
||||
dry_run=False,
|
||||
)
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user