feat(data): 为数据同步添加事务支持和同步日志
- Storage/ThreadSafeStorage 添加事务支持（begin/commit/rollback） - 新增 SyncLogManager 记录所有同步任务的执行状态 - 集成事务到 StockBasedSync、DateBasedSync、QuarterBasedSync - 在 sync_all 和 sync_financial 调度中心添加日志记录 - 新增测试验证事务和日志功能
This commit is contained in:
@@ -76,7 +76,11 @@ def get_stock_basic(
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return data
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def sync_all_stocks() -> pd.DataFrame:
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def sync_all_stocks(
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force_full: bool = False,
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dry_run: bool = False,
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**kwargs,
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) -> pd.DataFrame:
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"""Fetch and save all stocks (listed and delisted) to local storage.
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This is a special interface that should only be called once to initialize
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@@ -82,6 +82,9 @@ def sync_trade_cal_cache(
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start_date: str = "20180101",
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end_date: Optional[str] = None,
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force: bool = False,
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force_full: bool = False,
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dry_run: bool = False,
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**kwargs,
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) -> pd.DataFrame:
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"""Sync trade calendar data to local cache with incremental updates.
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@@ -25,6 +25,7 @@ from tqdm import tqdm
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from src.data.client import TushareClient
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from src.data.storage import ThreadSafeStorage, Storage
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from src.data.sync_logger import SyncLogManager
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from src.data.utils import get_today_date, get_quarters_in_range, DEFAULT_START_DATE
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@@ -466,18 +467,28 @@ class QuarterBasedSync(ABC):
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inserted_count = 0
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if is_first_sync_for_period:
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# 首次同步该季度：直接插入所有数据
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# 首次同步该季度：直接插入所有数据（使用事务）
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print(
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f"[{self.__class__.__name__}] First sync for quarter {period}, inserting all data directly"
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)
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if not dry_run:
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self.storage.queue_save(self.table_name, remote_df, use_upsert=False)
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self.storage.flush()
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inserted_count = len(remote_df)
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print(
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f"[{self.__class__.__name__}] Inserted {inserted_count} new records"
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)
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try:
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# 开始事务
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self.storage.begin_transaction()
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self.storage.queue_save(
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self.table_name, remote_df, use_upsert=False
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)
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self.storage.flush(use_transaction=False)
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self.storage.commit_transaction()
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inserted_count = len(remote_df)
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print(
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f"[{self.__class__.__name__}] Inserted {inserted_count} new records (transaction committed)"
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)
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except Exception as e:
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self.storage.rollback_transaction()
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print(f"[{self.__class__.__name__}] Transaction rolled back: {e}")
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raise
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return {
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"period": period,
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@@ -501,19 +512,33 @@ class QuarterBasedSync(ABC):
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print(f" - Unchanged stocks: {unchanged_count}")
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if not dry_run and not diff_df.empty:
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# 5.1 删除差异股票的旧数据
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deleted_stocks_count = len(diff_stocks)
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self.delete_stock_quarter_data(period, diff_stocks)
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deleted_count = len(diff_df)
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print(
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f"[{self.__class__.__name__}] Deleted {deleted_stocks_count} stocks' old records (approx {deleted_count} rows)"
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)
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try:
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# 开始事务
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self.storage.begin_transaction()
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# 5.2 插入新数据（使用普通 INSERT，因为已删除旧数据）
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self.storage.queue_save(self.table_name, diff_df, use_upsert=False)
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self.storage.flush()
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inserted_count = len(diff_df)
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print(f"[{self.__class__.__name__}] Inserted {inserted_count} new records")
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# 5.1 删除差异股票的旧数据
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deleted_stocks_count = len(diff_stocks)
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self.delete_stock_quarter_data(period, diff_stocks)
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deleted_count = len(diff_df)
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print(
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f"[{self.__class__.__name__}] Deleted {deleted_stocks_count} stocks' old records (approx {deleted_count} rows)"
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)
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# 5.2 插入新数据（使用普通 INSERT，因为已删除旧数据）
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self.storage.queue_save(self.table_name, diff_df, use_upsert=False)
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self.storage.flush(use_transaction=False)
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inserted_count = len(diff_df)
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# 提交事务
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self.storage.commit_transaction()
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print(
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f"[{self.__class__.__name__}] Inserted {inserted_count} new records (transaction committed)"
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)
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except Exception as e:
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self.storage.rollback_transaction()
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print(f"[{self.__class__.__name__}] Transaction rolled back: {e}")
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raise
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return {
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"period": period,
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@@ -583,55 +608,86 @@ class QuarterBasedSync(ABC):
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print(f"[{self.__class__.__name__}] Incremental Sync")
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print(f"{'=' * 60}")
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# 0. 确保表存在（首次同步时自动建表）
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self.ensure_table_exists()
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# 初始化日志管理器
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log_manager = SyncLogManager()
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log_entry = log_manager.start_sync(
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table_name=self.table_name,
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sync_type="incremental",
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metadata={"dry_run": dry_run},
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)
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# 1. 获取最新季度
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storage = Storage()
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try:
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result = storage._connection.execute(
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f'SELECT MAX(end_date) FROM "{self.table_name}"'
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).fetchone()
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latest_quarter = result[0] if result and result[0] else None
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if hasattr(latest_quarter, "strftime"):
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latest_quarter = latest_quarter.strftime("%Y%m%d")
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# 0. 确保表存在（首次同步时自动建表）
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self.ensure_table_exists()
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# 1. 获取最新季度
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storage = Storage()
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try:
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result = storage._connection.execute(
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f'SELECT MAX(end_date) FROM "{self.table_name}"'
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).fetchone()
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latest_quarter = result[0] if result and result[0] else None
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if hasattr(latest_quarter, "strftime"):
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latest_quarter = latest_quarter.strftime("%Y%m%d")
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except Exception as e:
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print(f"[{self.__class__.__name__}] Error getting latest quarter: {e}")
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latest_quarter = None
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# 2. 获取当前季度
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current_quarter = self.get_current_quarter()
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if latest_quarter is None:
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# 无本地数据，执行全量同步
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print(
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f"[{self.__class__.__name__}] No local data, performing full sync"
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)
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results = self.sync_range(
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self.DEFAULT_START_DATE, current_quarter, dry_run
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)
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else:
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print(
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f"[{self.__class__.__name__}] Latest local quarter: {latest_quarter}"
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)
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print(f"[{self.__class__.__name__}] Current quarter: {current_quarter}")
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# 3. 确定同步范围
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start_quarter = latest_quarter
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if start_quarter > current_quarter:
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start_quarter = current_quarter
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else:
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start_quarter = self.get_prev_quarter(latest_quarter)
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if start_quarter < self.DEFAULT_START_DATE:
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start_quarter = self.DEFAULT_START_DATE
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# 打印同步的两个季度信息
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print(f"\n[{self.__class__.__name__}] 将同步以下两个季度的财报:")
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print(f" - 前一季度: {start_quarter}")
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print(f" - 当前季度: {current_quarter}")
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print(f" (包含前一季度以确保数据完整性)")
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print()
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results = self.sync_range(start_quarter, current_quarter, dry_run)
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# 计算总插入记录数
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total_inserted = sum(
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r.get("inserted_count", 0) for r in results if isinstance(r, dict)
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)
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# 完成日志记录
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log_manager.complete_sync(
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log_entry,
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status="success",
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records_inserted=total_inserted,
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records_updated=0,
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records_deleted=0,
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)
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return results
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except Exception as e:
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print(f"[{self.__class__.__name__}] Error getting latest quarter: {e}")
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latest_quarter = None
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# 2. 获取当前季度
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current_quarter = self.get_current_quarter()
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if latest_quarter is None:
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# 无本地数据，执行全量同步
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print(f"[{self.__class__.__name__}] No local data, performing full sync")
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return self.sync_range(self.DEFAULT_START_DATE, current_quarter, dry_run)
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print(f"[{self.__class__.__name__}] Latest local quarter: {latest_quarter}")
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print(f"[{self.__class__.__name__}] Current quarter: {current_quarter}")
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# 3. 确定同步范围
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# 财务数据必须每次都进行对比更新，不存在"跳过"的情况
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# 同步范围：从最新季度到当前季度（包含前一季度以确保数据完整性）
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start_quarter = latest_quarter
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if start_quarter > current_quarter:
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# 如果本地数据比当前季度还新，仍然需要同步（可能包含修正数据）
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start_quarter = current_quarter
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else:
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# 正常情况：包含前一季度
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start_quarter = self.get_prev_quarter(latest_quarter)
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if start_quarter < self.DEFAULT_START_DATE:
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start_quarter = self.DEFAULT_START_DATE
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# 打印同步的两个季度信息
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print(f"\n[{self.__class__.__name__}] 将同步以下两个季度的财报:")
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print(f" - 前一季度: {start_quarter}")
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print(f" - 当前季度: {current_quarter}")
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print(f" (包含前一季度以确保数据完整性)")
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print()
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return self.sync_range(start_quarter, current_quarter, dry_run)
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log_manager.complete_sync(log_entry, status="failed", error_message=str(e))
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raise
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def sync_full(self, dry_run: bool = False) -> List[Dict]:
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"""执行全量同步。
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@@ -646,12 +702,38 @@ class QuarterBasedSync(ABC):
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print(f"[{self.__class__.__name__}] Full Sync")
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print(f"{'=' * 60}")
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# 确保表存在
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self.ensure_table_exists()
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# 初始化日志管理器
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log_manager = SyncLogManager()
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log_entry = log_manager.start_sync(
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table_name=self.table_name, sync_type="full", metadata={"dry_run": dry_run}
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)
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current_quarter = self.get_current_quarter()
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try:
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# 确保表存在
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self.ensure_table_exists()
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return self.sync_range(self.DEFAULT_START_DATE, current_quarter, dry_run)
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current_quarter = self.get_current_quarter()
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results = self.sync_range(self.DEFAULT_START_DATE, current_quarter, dry_run)
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# 计算总插入记录数
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total_inserted = sum(
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r.get("inserted_count", 0) for r in results if isinstance(r, dict)
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)
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# 完成日志记录
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log_manager.complete_sync(
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log_entry,
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status="success",
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records_inserted=total_inserted,
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records_updated=0,
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records_deleted=0,
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)
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return results
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except Exception as e:
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log_manager.complete_sync(log_entry, status="failed", error_message=str(e))
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raise
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# ======================================================================
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# 预览模式
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@@ -34,6 +34,7 @@ from tqdm import tqdm
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from src.data.client import TushareClient
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from src.data.storage import ThreadSafeStorage, Storage
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from src.data.sync_logger import SyncLogManager
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from src.data.utils import get_today_date, get_next_date
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from src.config.settings import get_settings
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from src.data.api_wrappers.api_trade_cal import (
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@@ -614,14 +615,30 @@ class StockBasedSync(BaseDataSync):
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finally:
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pbar.close()
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# 批量写入所有数据（仅在无错误时）
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# 批量写入所有数据（仅在无错误时），使用事务确保原子性
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if results and not error_occurred:
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for ts_code, data in results.items():
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if not data.empty:
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self.storage.queue_save(self.table_name, data)
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self.storage.flush()
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total_rows = sum(len(df) for df in results.values())
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print(f"\n[{class_name}] Saved {total_rows} rows to storage")
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try:
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# 开始事务
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self.storage.begin_transaction()
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for ts_code, data in results.items():
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if not data.empty:
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self.storage.queue_save(self.table_name, data)
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# flush 在事务中执行
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self.storage.flush(use_transaction=False)
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# 提交事务
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self.storage.commit_transaction()
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total_rows = sum(len(df) for df in results.values())
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print(
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f"\n[{class_name}] Saved {total_rows} rows to storage (transaction committed)"
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)
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except Exception as e:
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# 回滚事务
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self.storage.rollback_transaction()
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print(f"\n[{class_name}] Transaction rolled back due to error: {e}")
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error_occurred = True
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exception_to_raise = e
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# 打印摘要
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print(f"\n{'=' * 60}")
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@@ -824,6 +841,17 @@ class StockBasedSync(BaseDataSync):
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print(f"[{class_name}] Starting {self.table_name} data sync...")
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print(f"{'=' * 60}")
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# 初始化日志管理器并记录开始
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log_manager = SyncLogManager()
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sync_mode = "full" if force_full else "incremental"
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log_entry = log_manager.start_sync(
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table_name=self.table_name,
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sync_type=sync_mode,
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date_range_start=start_date,
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date_range_end=end_date,
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metadata={"dry_run": dry_run, "max_workers": max_workers},
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)
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# 首先确保交易日历缓存是最新的
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print(f"[{class_name}] Syncing trade calendar cache...")
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sync_trade_cal_cache()
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@@ -911,13 +939,33 @@ class StockBasedSync(BaseDataSync):
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print(f"[{class_name}] Using {max_workers or self.max_workers} worker threads")
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# 执行并发同步
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return self._run_concurrent_sync(
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stock_codes=stock_codes,
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start_date=sync_start_date,
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end_date=end_date,
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max_workers=max_workers,
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dry_run=dry_run,
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)
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try:
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results = self._run_concurrent_sync(
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stock_codes=stock_codes,
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start_date=sync_start_date,
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end_date=end_date,
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max_workers=max_workers,
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dry_run=dry_run,
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)
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# 计算同步结果统计
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total_inserted = sum(len(df) for df in results.values()) if results else 0
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# 完成日志记录
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log_manager.complete_sync(
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log_entry,
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status="success" if results else "partial",
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records_inserted=total_inserted,
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records_updated=0,
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records_deleted=0,
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)
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return results
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except Exception as e:
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# 记录失败日志
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log_manager.complete_sync(log_entry, status="failed", error_message=str(e))
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raise
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class DateBasedSync(BaseDataSync):
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@@ -1117,33 +1165,52 @@ class DateBasedSync(BaseDataSync):
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return combined
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def _save_data(self, data: pd.DataFrame, sync_start_date: str) -> None:
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"""保存数据到存储。
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def _save_data(self, data: pd.DataFrame, sync_start_date: str) -> int:
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"""保存数据到存储（使用事务确保原子性）。
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Args:
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data: 要保存的数据
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sync_start_date: 同步起始日期（用于删除旧数据）
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Returns:
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保存的记录数
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"""
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if data.empty:
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return
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return 0
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storage = Storage()
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storage = Storage(read_only=False)
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records_count = len(data)
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# 删除日期范围内的旧数据
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if sync_start_date:
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sync_start_date_fmt = pd.to_datetime(
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sync_start_date, format="%Y%m%d"
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).date()
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storage._connection.execute(
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f'DELETE FROM "{self.table_name}" WHERE "trade_date" >= ?',
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[sync_start_date_fmt],
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try:
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# 开始事务
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storage.begin_transaction()
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# 删除日期范围内的旧数据
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if sync_start_date:
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sync_start_date_fmt = pd.to_datetime(
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sync_start_date, format="%Y%m%d"
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).date()
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storage._connection.execute(
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f'DELETE FROM "{self.table_name}" WHERE "trade_date" >= ?',
|
||||
[sync_start_date_fmt],
|
||||
)
|
||||
|
||||
# 保存新数据（在事务中直接保存，不使用队列）
|
||||
storage.save(self.table_name, data, mode="append")
|
||||
|
||||
# 提交事务
|
||||
storage.commit_transaction()
|
||||
print(
|
||||
f"[{self.__class__.__name__}] Saved {records_count} records to DuckDB (transaction committed)"
|
||||
)
|
||||
return records_count
|
||||
|
||||
# 保存新数据
|
||||
self.storage.queue_save(self.table_name, data)
|
||||
self.storage.flush()
|
||||
|
||||
print(f"[{self.__class__.__name__}] Saved {len(data)} records to DuckDB")
|
||||
except Exception as e:
|
||||
storage.rollback_transaction()
|
||||
print(
|
||||
f"[{self.__class__.__name__}] Transaction rolled back due to error: {e}"
|
||||
)
|
||||
raise
|
||||
|
||||
def preview_sync(
|
||||
self,
|
||||
@@ -1280,12 +1347,25 @@ class DateBasedSync(BaseDataSync):
|
||||
print(f"[{class_name}] Starting {self.table_name} data sync...")
|
||||
print(f"{'=' * 60}")
|
||||
|
||||
# 初始化日志管理器并记录开始
|
||||
log_manager = SyncLogManager()
|
||||
sync_mode = "full" if force_full else "incremental"
|
||||
log_entry = log_manager.start_sync(
|
||||
table_name=self.table_name,
|
||||
sync_type=sync_mode,
|
||||
date_range_start=start_date,
|
||||
date_range_end=end_date,
|
||||
metadata={"dry_run": dry_run},
|
||||
)
|
||||
|
||||
# 确定日期范围
|
||||
sync_start, sync_end, mode = self._get_sync_date_range(
|
||||
start_date, end_date, force_full
|
||||
)
|
||||
|
||||
if mode == "up_to_date":
|
||||
# 记录跳过日志
|
||||
log_manager.complete_sync(log_entry, status="success", records_inserted=0)
|
||||
return pd.DataFrame()
|
||||
|
||||
if dry_run:
|
||||
@@ -1295,49 +1375,74 @@ class DateBasedSync(BaseDataSync):
|
||||
print(f" Would sync from {sync_start} to {sync_end}")
|
||||
print(f" Mode: {mode}")
|
||||
print(f"{'=' * 60}")
|
||||
# 记录 dry run 日志
|
||||
log_manager.complete_sync(log_entry, status="success", records_inserted=0)
|
||||
return pd.DataFrame()
|
||||
|
||||
# 检查表是否存在，不存在则创建
|
||||
storage = Storage()
|
||||
if not storage.exists(self.table_name):
|
||||
print(
|
||||
f"[{class_name}] Table '{self.table_name}' doesn't exist, creating..."
|
||||
try:
|
||||
# 检查表是否存在，不存在则创建
|
||||
storage = Storage()
|
||||
if not storage.exists(self.table_name):
|
||||
print(
|
||||
f"[{class_name}] Table '{self.table_name}' doesn't exist, creating..."
|
||||
)
|
||||
# 获取样本数据以推断 schema
|
||||
sample = self.fetch_single_date(sync_end)
|
||||
if sample.empty:
|
||||
# 尝试另一个日期
|
||||
sample = self.fetch_single_date("20240102")
|
||||
if not sample.empty:
|
||||
self._ensure_table_schema(sample)
|
||||
else:
|
||||
print(
|
||||
f"[{class_name}] Cannot create table: no sample data available"
|
||||
)
|
||||
log_manager.complete_sync(
|
||||
log_entry,
|
||||
status="failed",
|
||||
error_message="No sample data available",
|
||||
)
|
||||
return pd.DataFrame()
|
||||
|
||||
# 首次同步探测：验证表结构是否正常
|
||||
if self._should_probe_table():
|
||||
print(f"[{class_name}] Table '{self.table_name}' is empty, probing...")
|
||||
# 使用最近一个交易日的完整数据进行探测
|
||||
probe_date = get_last_trading_day(sync_start, sync_end)
|
||||
if probe_date:
|
||||
probe_data = self.fetch_single_date(probe_date)
|
||||
probe_desc = f"date={probe_date}, all stocks"
|
||||
self._probe_table_and_cleanup(probe_data, probe_desc)
|
||||
|
||||
# 执行同步
|
||||
combined = self._run_date_range_sync(sync_start, sync_end, dry_run)
|
||||
|
||||
# 保存数据（在事务中）
|
||||
records_saved = 0
|
||||
if not combined.empty:
|
||||
records_saved = self._save_data(combined, sync_start)
|
||||
|
||||
# 打印摘要
|
||||
print(f"\n{'=' * 60}")
|
||||
print(f"[{class_name}] Sync Summary")
|
||||
print(f"{'=' * 60}")
|
||||
print(f" Mode: {mode}")
|
||||
print(f" Date range: {sync_start} to {sync_end}")
|
||||
print(f" Records: {len(combined)}")
|
||||
print(f"{'=' * 60}")
|
||||
|
||||
# 完成日志记录
|
||||
log_manager.complete_sync(
|
||||
log_entry,
|
||||
status="success",
|
||||
records_inserted=records_saved,
|
||||
records_updated=0,
|
||||
records_deleted=0,
|
||||
)
|
||||
# 获取样本数据以推断 schema
|
||||
sample = self.fetch_single_date(sync_end)
|
||||
if sample.empty:
|
||||
# 尝试另一个日期
|
||||
sample = self.fetch_single_date("20240102")
|
||||
if not sample.empty:
|
||||
self._ensure_table_schema(sample)
|
||||
else:
|
||||
print(f"[{class_name}] Cannot create table: no sample data available")
|
||||
return pd.DataFrame()
|
||||
|
||||
# 首次同步探测：验证表结构是否正常
|
||||
if self._should_probe_table():
|
||||
print(f"[{class_name}] Table '{self.table_name}' is empty, probing...")
|
||||
# 使用最近一个交易日的完整数据进行探测
|
||||
probe_date = get_last_trading_day(sync_start, sync_end)
|
||||
if probe_date:
|
||||
probe_data = self.fetch_single_date(probe_date)
|
||||
probe_desc = f"date={probe_date}, all stocks"
|
||||
self._probe_table_and_cleanup(probe_data, probe_desc)
|
||||
return combined
|
||||
|
||||
# 执行同步
|
||||
combined = self._run_date_range_sync(sync_start, sync_end, dry_run)
|
||||
|
||||
# 保存数据
|
||||
if not combined.empty:
|
||||
self._save_data(combined, sync_start)
|
||||
|
||||
# 打印摘要
|
||||
print(f"\n{'=' * 60}")
|
||||
print(f"[{class_name}] Sync Summary")
|
||||
print(f"{'=' * 60}")
|
||||
print(f" Mode: {mode}")
|
||||
print(f" Date range: {sync_start} to {sync_end}")
|
||||
print(f" Records: {len(combined)}")
|
||||
print(f"{'=' * 60}")
|
||||
|
||||
return combined
|
||||
except Exception as e:
|
||||
# 记录失败日志
|
||||
log_manager.complete_sync(log_entry, status="failed", error_message=str(e))
|
||||
raise
|
||||
|
||||
@@ -36,6 +36,7 @@
|
||||
|
||||
from typing import List, Optional
|
||||
|
||||
from src.data.sync_logger import SyncLogManager
|
||||
from src.data.api_wrappers.financial_data.api_income import (
|
||||
IncomeQuarterSync,
|
||||
sync_income,
|
||||
@@ -120,6 +121,14 @@ def sync_financial(
|
||||
|
||||
results = {}
|
||||
|
||||
# 初始化日志管理器并记录调度中心开始
|
||||
log_manager = SyncLogManager()
|
||||
log_entry = log_manager.start_sync(
|
||||
table_name="financial_data_batch",
|
||||
sync_type="full" if force_full else "incremental",
|
||||
metadata={"data_types": data_types, "dry_run": dry_run},
|
||||
)
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("[Financial Sync] 财务数据同步调度中心")
|
||||
print("=" * 60)
|
||||
@@ -128,10 +137,14 @@ def sync_financial(
|
||||
print(f"写入模式: {'预览' if dry_run else '实际写入'}")
|
||||
print("=" * 60)
|
||||
|
||||
total_inserted = 0
|
||||
failed_types = []
|
||||
|
||||
for data_type in data_types:
|
||||
if data_type not in FINANCIAL_SYNCERS:
|
||||
print(f"[WARN] 未知的数据类型: {data_type}")
|
||||
results[data_type] = {"error": f"Unknown data type: {data_type}"}
|
||||
failed_types.append(data_type)
|
||||
continue
|
||||
|
||||
config = FINANCIAL_SYNCERS[data_type]
|
||||
@@ -143,10 +156,19 @@ def sync_financial(
|
||||
try:
|
||||
result = sync_func(force_full=force_full, dry_run=dry_run)
|
||||
results[data_type] = result
|
||||
|
||||
# 统计插入的记录数
|
||||
if isinstance(result, list):
|
||||
inserted = sum(
|
||||
r.get("inserted_count", 0) for r in result if isinstance(r, dict)
|
||||
)
|
||||
total_inserted += inserted
|
||||
|
||||
print(f"[{display_name}] 同步完成")
|
||||
except Exception as e:
|
||||
print(f"[ERROR] [{display_name}] 同步失败: {e}")
|
||||
results[data_type] = {"error": str(e)}
|
||||
failed_types.append(data_type)
|
||||
|
||||
# 打印汇总
|
||||
print("\n" + "=" * 60)
|
||||
@@ -169,6 +191,16 @@ def sync_financial(
|
||||
print(f" {display_name}: {status}")
|
||||
print("=" * 60)
|
||||
|
||||
# 完成调度中心日志记录
|
||||
status = "failed" if failed_types else "success"
|
||||
error_msg = f"Failed types: {failed_types}" if failed_types else None
|
||||
log_manager.complete_sync(
|
||||
log_entry,
|
||||
status=status,
|
||||
records_inserted=total_inserted,
|
||||
error_message=error_msg,
|
||||
)
|
||||
|
||||
return results
|
||||
|
||||
|
||||
|
||||
@@ -313,6 +313,87 @@ class Storage:
|
||||
Storage._connection = None
|
||||
Storage._instance = None
|
||||
|
||||
# ======================================================================
|
||||
# 事务支持
|
||||
# ======================================================================
|
||||
|
||||
def begin_transaction(self) -> None:
|
||||
"""开始事务。
|
||||
|
||||
使用方式:
|
||||
storage = Storage(read_only=False)
|
||||
storage.begin_transaction()
|
||||
try:
|
||||
storage.save("table1", data1)
|
||||
storage.save("table2", data2)
|
||||
storage.commit_transaction()
|
||||
except Exception:
|
||||
storage.rollback_transaction()
|
||||
raise
|
||||
"""
|
||||
if self._read_only:
|
||||
raise RuntimeError("Cannot begin transaction in read-only mode")
|
||||
|
||||
try:
|
||||
self._connection.execute("BEGIN TRANSACTION")
|
||||
print("[Storage] Transaction started")
|
||||
except Exception as e:
|
||||
print(f"[Storage] Error starting transaction: {e}")
|
||||
raise
|
||||
|
||||
def commit_transaction(self) -> None:
|
||||
"""提交事务。"""
|
||||
if self._read_only:
|
||||
return
|
||||
|
||||
try:
|
||||
self._connection.execute("COMMIT")
|
||||
print("[Storage] Transaction committed")
|
||||
except Exception as e:
|
||||
print(f"[Storage] Error committing transaction: {e}")
|
||||
raise
|
||||
|
||||
def rollback_transaction(self) -> None:
|
||||
"""回滚事务。"""
|
||||
if self._read_only:
|
||||
return
|
||||
|
||||
try:
|
||||
self._connection.execute("ROLLBACK")
|
||||
print("[Storage] Transaction rolled back")
|
||||
except Exception as e:
|
||||
print(f"[Storage] Error rolling back transaction: {e}")
|
||||
|
||||
def transaction(self):
|
||||
"""事务上下文管理器。
|
||||
|
||||
使用方式:
|
||||
storage = Storage(read_only=False)
|
||||
with storage.transaction():
|
||||
storage.save("table1", data1)
|
||||
storage.save("table2", data2)
|
||||
# 自动提交或回滚
|
||||
"""
|
||||
return _TransactionContext(self)
|
||||
|
||||
|
||||
class _TransactionContext:
|
||||
"""事务上下文管理器。"""
|
||||
|
||||
def __init__(self, storage: Storage):
|
||||
self.storage = storage
|
||||
|
||||
def __enter__(self):
|
||||
self.storage.begin_transaction()
|
||||
return self.storage
|
||||
|
||||
def __exit__(self, exc_type, exc_val, exc_tb):
|
||||
if exc_type is None:
|
||||
self.storage.commit_transaction()
|
||||
else:
|
||||
self.storage.rollback_transaction()
|
||||
return False
|
||||
|
||||
|
||||
class ThreadSafeStorage:
|
||||
"""线程安全的 DuckDB 写入包装器。
|
||||
@@ -323,12 +404,14 @@ class ThreadSafeStorage:
|
||||
注意：
|
||||
- 此类自动使用 read_only=False 模式，用于数据同步
|
||||
- 不要在多进程中同时使用此类，只应在单进程中用于批量写入
|
||||
- 支持事务模式：在事务中批量写入，确保原子性
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
# 使用 read_only=False 模式创建 Storage，用于写入操作
|
||||
self.storage = Storage(read_only=False)
|
||||
self._pending_writes: List[tuple] = [] # [(name, data, use_upsert), ...]
|
||||
self._in_transaction: bool = False
|
||||
|
||||
def queue_save(self, name: str, data: pd.DataFrame, use_upsert: bool = True):
|
||||
"""将数据放入写入队列（不立即写入）
|
||||
@@ -341,10 +424,13 @@ class ThreadSafeStorage:
|
||||
if not data.empty:
|
||||
self._pending_writes.append((name, data, use_upsert))
|
||||
|
||||
def flush(self):
|
||||
def flush(self, use_transaction: bool = True):
|
||||
"""批量写入所有队列数据。
|
||||
|
||||
调用时机：在 sync 结束时统一调用，避免并发写入冲突。
|
||||
|
||||
Args:
|
||||
use_transaction: 若为 True，使用事务包装批量写入
|
||||
"""
|
||||
if not self._pending_writes:
|
||||
return
|
||||
@@ -357,17 +443,72 @@ class ThreadSafeStorage:
|
||||
table_data[key].append(data)
|
||||
|
||||
# 批量写入每个表
|
||||
for (name, use_upsert), data_list in table_data.items():
|
||||
combined = pd.concat(data_list, ignore_index=True)
|
||||
# 在批量数据中先去重
|
||||
if "ts_code" in combined.columns and "trade_date" in combined.columns:
|
||||
combined = combined.drop_duplicates(
|
||||
subset=["ts_code", "trade_date"], keep="last"
|
||||
if use_transaction:
|
||||
# 使用事务确保原子性
|
||||
try:
|
||||
self.storage.begin_transaction()
|
||||
total_rows = 0
|
||||
|
||||
for (name, use_upsert), data_list in table_data.items():
|
||||
combined = pd.concat(data_list, ignore_index=True)
|
||||
# 在批量数据中先去重
|
||||
if (
|
||||
"ts_code" in combined.columns
|
||||
and "trade_date" in combined.columns
|
||||
):
|
||||
combined = combined.drop_duplicates(
|
||||
subset=["ts_code", "trade_date"], keep="last"
|
||||
)
|
||||
result = self.storage.save(
|
||||
name, combined, mode="append", use_upsert=use_upsert
|
||||
)
|
||||
if result.get("status") == "success":
|
||||
total_rows += result.get("rows", 0)
|
||||
|
||||
self.storage.commit_transaction()
|
||||
print(
|
||||
f"[ThreadSafeStorage] Transaction committed: {total_rows} rows saved"
|
||||
)
|
||||
self.storage.save(name, combined, mode="append", use_upsert=use_upsert)
|
||||
|
||||
except Exception as e:
|
||||
self.storage.rollback_transaction()
|
||||
print(f"[ThreadSafeStorage] Transaction rolled back due to error: {e}")
|
||||
raise
|
||||
else:
|
||||
# 不使用事务，逐表写入
|
||||
for (name, use_upsert), data_list in table_data.items():
|
||||
combined = pd.concat(data_list, ignore_index=True)
|
||||
# 在批量数据中先去重
|
||||
if "ts_code" in combined.columns and "trade_date" in combined.columns:
|
||||
combined = combined.drop_duplicates(
|
||||
subset=["ts_code", "trade_date"], keep="last"
|
||||
)
|
||||
self.storage.save(name, combined, mode="append", use_upsert=use_upsert)
|
||||
|
||||
self._pending_writes.clear()
|
||||
|
||||
def begin_transaction(self) -> None:
|
||||
"""开始事务模式。
|
||||
|
||||
在事务模式下，flush 会被延迟到 commit_transaction 或 rollback_transaction。
|
||||
"""
|
||||
self._in_transaction = True
|
||||
self.storage.begin_transaction()
|
||||
|
||||
def commit_transaction(self) -> None:
|
||||
"""提交事务。"""
|
||||
if self._pending_writes:
|
||||
# 先写入队列中的数据
|
||||
self.flush(use_transaction=False)
|
||||
self.storage.commit_transaction()
|
||||
self._in_transaction = False
|
||||
|
||||
def rollback_transaction(self) -> None:
|
||||
"""回滚事务。"""
|
||||
self._pending_writes.clear()
|
||||
self.storage.rollback_transaction()
|
||||
self._in_transaction = False
|
||||
|
||||
def __getattr__(self, name):
|
||||
"""代理其他方法到 Storage 实例"""
|
||||
return getattr(self.storage, name)
|
||||
|
||||
@@ -55,6 +55,7 @@ import pandas as pd
|
||||
from src.data import api_wrappers # noqa: F401
|
||||
from src.data.sync_registry import sync_registry
|
||||
from src.data.api_wrappers import sync_all_stocks
|
||||
from src.data.sync_logger import SyncLogManager
|
||||
|
||||
|
||||
def sync_all_data(
|
||||
@@ -109,7 +110,7 @@ def sync_all_data(
|
||||
>>> result = sync_all_data(dry_run=True)
|
||||
>>>
|
||||
>>> # 只同步特定任务
|
||||
>>> result = sync_all_data(selected=["trade_cal", "stock_basic"])
|
||||
>>> result = sync_all_data(selected=['trade_cal', 'pro_bar'])
|
||||
>>>
|
||||
>>> # 查看所有可用任务
|
||||
>>> from src.data.sync_registry import sync_registry
|
||||
@@ -117,13 +118,80 @@ def sync_all_data(
|
||||
>>> for t in tasks:
|
||||
... print(f"{t.name}: {t.display_name}")
|
||||
"""
|
||||
return sync_registry.sync_all(
|
||||
force_full=force_full,
|
||||
max_workers=max_workers,
|
||||
dry_run=dry_run,
|
||||
selected=selected,
|
||||
# 记录调度中心开始
|
||||
log_manager = SyncLogManager()
|
||||
sync_mode = "full" if force_full else "incremental"
|
||||
selected_str = ",".join(selected) if selected else "all"
|
||||
log_manager.start_sync(
|
||||
table_name="daily_data_batch",
|
||||
sync_type=sync_mode,
|
||||
metadata={
|
||||
"selected": selected_str,
|
||||
"dry_run": dry_run,
|
||||
"max_workers": max_workers,
|
||||
},
|
||||
)
|
||||
|
||||
try:
|
||||
result = sync_registry.sync_all(
|
||||
force_full=force_full,
|
||||
max_workers=max_workers,
|
||||
dry_run=dry_run,
|
||||
selected=selected,
|
||||
)
|
||||
|
||||
# 计算成功/失败数量
|
||||
success_count = 0
|
||||
failed_count = 0
|
||||
total_records = 0
|
||||
for task_name, task_result in result.items():
|
||||
if isinstance(task_result, dict):
|
||||
if task_result.get("status") == "error":
|
||||
failed_count += 1
|
||||
else:
|
||||
success_count += 1
|
||||
# 累加记录数（如果有）
|
||||
if "rows" in task_result:
|
||||
total_records += task_result.get("rows", 0)
|
||||
elif isinstance(task_result, pd.DataFrame):
|
||||
success_count += 1
|
||||
total_records += len(task_result)
|
||||
else:
|
||||
success_count += 1
|
||||
|
||||
# 记录完成日志
|
||||
status = "partial" if failed_count > 0 else "success"
|
||||
error_msg = f"Failed: {failed_count} tasks" if failed_count > 0 else None
|
||||
log_manager.complete_sync(
|
||||
table_name="daily_data_batch",
|
||||
sync_type=sync_mode,
|
||||
status=status,
|
||||
records_inserted=total_records,
|
||||
error_message=error_msg,
|
||||
metadata={
|
||||
"selected": selected_str,
|
||||
"dry_run": dry_run,
|
||||
"max_workers": max_workers,
|
||||
},
|
||||
)
|
||||
|
||||
return result
|
||||
|
||||
except Exception as e:
|
||||
# 记录失败日志
|
||||
log_manager.complete_sync(
|
||||
table_name="daily_data_batch",
|
||||
sync_type=sync_mode,
|
||||
status="failed",
|
||||
error_message=str(e),
|
||||
metadata={
|
||||
"selected": selected_str,
|
||||
"dry_run": dry_run,
|
||||
"max_workers": max_workers,
|
||||
},
|
||||
)
|
||||
raise
|
||||
|
||||
|
||||
def list_sync_tasks() -> list[dict[str, Any]]:
|
||||
"""列出所有已注册的同步任务。
|
||||
|
||||
439
src/data/sync_logger.py
Normal file
439
src/data/sync_logger.py
Normal file
@@ -0,0 +1,439 @@
|
||||
"""同步日志管理模块。
|
||||
|
||||
提供同步操作日志记录和查询功能，追踪每次数据同步的详细信息。
|
||||
设计理念：日志只插入不更新，无需主键 ID。
|
||||
"""
|
||||
|
||||
from datetime import datetime
|
||||
from typing import Optional, Dict, Any, List
|
||||
import pandas as pd
|
||||
from dataclasses import dataclass
|
||||
|
||||
from src.data.storage import Storage
|
||||
|
||||
|
||||
@dataclass
|
||||
class SyncLogEntry:
|
||||
"""同步日志条目。
|
||||
|
||||
Attributes:
|
||||
table_name: 同步的表名
|
||||
sync_type: 同步类型（full/incremental/quarterly/daily 等）
|
||||
start_time: 同步开始时间
|
||||
end_time: 同步结束时间
|
||||
status: 同步状态（success/failed/partial/running）
|
||||
records_before: 同步前记录数
|
||||
records_after: 同步后记录数
|
||||
records_inserted: 插入的记录数
|
||||
records_updated: 更新的记录数
|
||||
records_deleted: 删除的记录数
|
||||
date_range_start: 数据日期范围起始
|
||||
date_range_end: 数据日期范围结束
|
||||
error_message: 错误信息（如果有）
|
||||
metadata: 额外元数据（JSON 格式）
|
||||
"""
|
||||
|
||||
table_name: str
|
||||
sync_type: str
|
||||
start_time: datetime
|
||||
end_time: Optional[datetime] = None
|
||||
status: str = "running"
|
||||
records_before: int = 0
|
||||
records_after: int = 0
|
||||
records_inserted: int = 0
|
||||
records_updated: int = 0
|
||||
records_deleted: int = 0
|
||||
date_range_start: Optional[str] = None
|
||||
date_range_end: Optional[str] = None
|
||||
error_message: Optional[str] = None
|
||||
metadata: Optional[str] = None
|
||||
|
||||
|
||||
class SyncLogManager:
|
||||
"""同步日志管理器。
|
||||
|
||||
管理同步日志表的创建、记录插入和查询。
|
||||
设计原则：日志只插入，不更新，无需主键。
|
||||
|
||||
使用方式:
|
||||
# 记录一次同步操作（开始和结束分别记录）
|
||||
log_manager = SyncLogManager()
|
||||
log_manager.start_sync("daily", "incremental") # 记录开始
|
||||
try:
|
||||
# 执行同步...
|
||||
log_manager.complete_sync("daily", "success", records_inserted=1000) # 记录完成
|
||||
except Exception as e:
|
||||
log_manager.complete_sync("daily", "failed", error_message=str(e)) # 记录失败
|
||||
|
||||
# 查询同步历史
|
||||
logs = log_manager.get_sync_history("daily", limit=10)
|
||||
"""
|
||||
|
||||
TABLE_NAME = "_sync_logs"
|
||||
|
||||
def __init__(self, storage: Optional[Storage] = None):
|
||||
"""初始化日志管理器。
|
||||
|
||||
Args:
|
||||
storage: Storage 实例，如果为 None 则创建新实例
|
||||
"""
|
||||
self.storage = storage or Storage(read_only=False)
|
||||
self._ensure_table_exists()
|
||||
|
||||
def _ensure_table_exists(self) -> None:
|
||||
"""确保日志表存在。"""
|
||||
create_sql = f"""
|
||||
CREATE TABLE IF NOT EXISTS {self.TABLE_NAME} (
|
||||
table_name VARCHAR(64) NOT NULL,
|
||||
sync_type VARCHAR(32) NOT NULL,
|
||||
start_time TIMESTAMP NOT NULL,
|
||||
end_time TIMESTAMP,
|
||||
status VARCHAR(16) DEFAULT 'running',
|
||||
records_before INTEGER DEFAULT 0,
|
||||
records_after INTEGER DEFAULT 0,
|
||||
records_inserted INTEGER DEFAULT 0,
|
||||
records_updated INTEGER DEFAULT 0,
|
||||
records_deleted INTEGER DEFAULT 0,
|
||||
date_range_start VARCHAR(8),
|
||||
date_range_end VARCHAR(8),
|
||||
error_message TEXT,
|
||||
metadata TEXT,
|
||||
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
|
||||
)
|
||||
"""
|
||||
|
||||
# 创建索引
|
||||
index_sql = f"""
|
||||
CREATE INDEX IF NOT EXISTS idx_sync_logs_table_time
|
||||
ON {self.TABLE_NAME}(table_name, start_time DESC);
|
||||
|
||||
CREATE INDEX IF NOT EXISTS idx_sync_logs_status
|
||||
ON {self.TABLE_NAME}(status);
|
||||
|
||||
CREATE INDEX IF NOT EXISTS idx_sync_logs_type_time
|
||||
ON {self.TABLE_NAME}(sync_type, start_time DESC);
|
||||
"""
|
||||
|
||||
try:
|
||||
self.storage._connection.execute(create_sql)
|
||||
self.storage._connection.execute(index_sql)
|
||||
except Exception as e:
|
||||
print(f"[SyncLogManager] Error creating log table: {e}")
|
||||
raise
|
||||
|
||||
def start_sync(
|
||||
self,
|
||||
table_name: str,
|
||||
sync_type: str,
|
||||
date_range_start: Optional[str] = None,
|
||||
date_range_end: Optional[str] = None,
|
||||
metadata: Optional[Dict[str, Any]] = None,
|
||||
) -> None:
|
||||
"""记录同步开始。
|
||||
|
||||
Args:
|
||||
table_name: 同步的表名
|
||||
sync_type: 同步类型（full/incremental/quarterly 等）
|
||||
date_range_start: 数据日期范围起始
|
||||
date_range_end: 数据日期范围结束
|
||||
metadata: 额外元数据字典
|
||||
"""
|
||||
entry = SyncLogEntry(
|
||||
table_name=table_name,
|
||||
sync_type=sync_type,
|
||||
start_time=datetime.now(),
|
||||
status="running",
|
||||
records_before=0, # 不统计记录数，避免额外查询
|
||||
date_range_start=date_range_start,
|
||||
date_range_end=date_range_end,
|
||||
metadata=str(metadata) if metadata else None,
|
||||
)
|
||||
|
||||
try:
|
||||
self.storage._connection.execute(
|
||||
f"""
|
||||
INSERT INTO {self.TABLE_NAME} (
|
||||
table_name, sync_type, start_time, status,
|
||||
records_before, date_range_start, date_range_end, metadata
|
||||
) VALUES (?, ?, ?, ?, ?, ?, ?, ?)
|
||||
""",
|
||||
(
|
||||
entry.table_name,
|
||||
entry.sync_type,
|
||||
entry.start_time,
|
||||
entry.status,
|
||||
entry.records_before,
|
||||
entry.date_range_start,
|
||||
entry.date_range_end,
|
||||
entry.metadata,
|
||||
),
|
||||
)
|
||||
except Exception as e:
|
||||
print(f"[SyncLogManager] Error logging sync start: {e}")
|
||||
|
||||
def complete_sync(
|
||||
self,
|
||||
table_name: str,
|
||||
status: str = "success",
|
||||
records_inserted: int = 0,
|
||||
records_updated: int = 0,
|
||||
records_deleted: int = 0,
|
||||
error_message: Optional[str] = None,
|
||||
sync_type: str = "incremental",
|
||||
date_range_start: Optional[str] = None,
|
||||
date_range_end: Optional[str] = None,
|
||||
metadata: Optional[Dict[str, Any]] = None,
|
||||
) -> None:
|
||||
"""记录同步完成。
|
||||
|
||||
作为一条新的日志记录插入，不更新之前的记录。
|
||||
|
||||
Args:
|
||||
table_name: 同步的表名
|
||||
status: 同步状态（success/failed/partial）
|
||||
records_inserted: 插入的记录数
|
||||
records_updated: 更新的记录数
|
||||
records_deleted: 删除的记录数
|
||||
error_message: 错误信息（如果失败）
|
||||
sync_type: 同步类型
|
||||
date_range_start: 日期范围起始
|
||||
date_range_end: 日期范围结束
|
||||
metadata: 元数据
|
||||
"""
|
||||
entry = SyncLogEntry(
|
||||
table_name=table_name,
|
||||
sync_type=sync_type,
|
||||
start_time=datetime.now(),
|
||||
end_time=datetime.now(),
|
||||
status=status,
|
||||
records_inserted=records_inserted,
|
||||
records_updated=records_updated,
|
||||
records_deleted=records_deleted,
|
||||
date_range_start=date_range_start,
|
||||
date_range_end=date_range_end,
|
||||
error_message=error_message,
|
||||
metadata=str(metadata) if metadata else None,
|
||||
)
|
||||
|
||||
try:
|
||||
self.storage._connection.execute(
|
||||
f"""
|
||||
INSERT INTO {self.TABLE_NAME} (
|
||||
table_name, sync_type, start_time, end_time, status,
|
||||
records_inserted, records_updated, records_deleted,
|
||||
date_range_start, date_range_end, error_message, metadata
|
||||
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
|
||||
""",
|
||||
(
|
||||
entry.table_name,
|
||||
entry.sync_type,
|
||||
entry.start_time,
|
||||
entry.end_time,
|
||||
entry.status,
|
||||
entry.records_inserted,
|
||||
entry.records_updated,
|
||||
entry.records_deleted,
|
||||
entry.date_range_start,
|
||||
entry.date_range_end,
|
||||
entry.error_message,
|
||||
entry.metadata,
|
||||
),
|
||||
)
|
||||
except Exception as e:
|
||||
print(f"[SyncLogManager] Error logging sync complete: {e}")
|
||||
|
||||
def get_sync_history(
|
||||
self,
|
||||
table_name: Optional[str] = None,
|
||||
status: Optional[str] = None,
|
||||
limit: int = 100,
|
||||
offset: int = 0,
|
||||
) -> pd.DataFrame:
|
||||
"""查询同步历史。
|
||||
|
||||
Args:
|
||||
table_name: 按表名过滤
|
||||
status: 按状态过滤
|
||||
limit: 返回记录数限制
|
||||
offset: 分页偏移
|
||||
|
||||
Returns:
|
||||
同步历史 DataFrame
|
||||
"""
|
||||
conditions = []
|
||||
params = []
|
||||
|
||||
if table_name:
|
||||
conditions.append("table_name = ?")
|
||||
params.append(table_name)
|
||||
|
||||
if status:
|
||||
conditions.append("status = ?")
|
||||
params.append(status)
|
||||
|
||||
where_clause = f"WHERE {' AND '.join(conditions)}" if conditions else ""
|
||||
|
||||
query = f"""
|
||||
SELECT * FROM {self.TABLE_NAME}
|
||||
{where_clause}
|
||||
ORDER BY start_time DESC
|
||||
LIMIT ? OFFSET ?
|
||||
"""
|
||||
params.extend([limit, offset])
|
||||
|
||||
try:
|
||||
return self.storage._connection.execute(query, params).fetchdf()
|
||||
except Exception as e:
|
||||
print(f"[SyncLogManager] Error querying sync history: {e}")
|
||||
return pd.DataFrame()
|
||||
|
||||
def get_last_sync(
|
||||
self, table_name: str, status: Optional[str] = "success"
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
"""获取指定表的最近一次同步记录。
|
||||
|
||||
Args:
|
||||
table_name: 表名
|
||||
status: 状态过滤，None 表示不限制
|
||||
|
||||
Returns:
|
||||
同步记录字典，如果没有则返回 None
|
||||
"""
|
||||
conditions = ["table_name = ?"]
|
||||
params = [table_name]
|
||||
|
||||
if status:
|
||||
conditions.append("status = ?")
|
||||
params.append(status)
|
||||
|
||||
query = f"""
|
||||
SELECT * FROM {self.TABLE_NAME}
|
||||
WHERE {" AND ".join(conditions)}
|
||||
ORDER BY start_time DESC
|
||||
LIMIT 1
|
||||
"""
|
||||
|
||||
try:
|
||||
df = self.storage._connection.execute(query, params).fetchdf()
|
||||
if not df.empty:
|
||||
return df.iloc[0].to_dict()
|
||||
return None
|
||||
except Exception as e:
|
||||
print(f"[SyncLogManager] Error getting last sync: {e}")
|
||||
return None
|
||||
|
||||
def get_sync_summary(
|
||||
self, table_name: Optional[str] = None, days: int = 30
|
||||
) -> Dict[str, Any]:
|
||||
"""获取同步汇总统计。
|
||||
|
||||
Args:
|
||||
table_name: 按表名过滤
|
||||
days: 最近多少天的统计
|
||||
|
||||
Returns:
|
||||
汇总统计字典
|
||||
"""
|
||||
conditions = [f"start_time >= CURRENT_DATE - INTERVAL '{days} days'"]
|
||||
params = []
|
||||
|
||||
if table_name:
|
||||
conditions.append("table_name = ?")
|
||||
params.append(table_name)
|
||||
|
||||
where_clause = f"WHERE {' AND '.join(conditions)}"
|
||||
|
||||
query = f"""
|
||||
SELECT
|
||||
COUNT(*) as total_syncs,
|
||||
COUNT(CASE WHEN status = 'success' THEN 1 END) as success_count,
|
||||
COUNT(CASE WHEN status = 'failed' THEN 1 END) as failed_count,
|
||||
COUNT(CASE WHEN status = 'partial' THEN 1 END) as partial_count,
|
||||
SUM(records_inserted) as total_inserted,
|
||||
SUM(records_updated) as total_updated,
|
||||
SUM(records_deleted) as total_deleted
|
||||
FROM {self.TABLE_NAME}
|
||||
{where_clause}
|
||||
"""
|
||||
|
||||
try:
|
||||
df = self.storage._connection.execute(query, params).fetchdf()
|
||||
if not df.empty:
|
||||
return {
|
||||
"total_syncs": int(df.iloc[0]["total_syncs"]),
|
||||
"success_count": int(df.iloc[0]["success_count"]),
|
||||
"failed_count": int(df.iloc[0]["failed_count"]),
|
||||
"partial_count": int(df.iloc[0]["partial_count"]),
|
||||
"total_inserted": int(df.iloc[0]["total_inserted"] or 0),
|
||||
"total_updated": int(df.iloc[0]["total_updated"] or 0),
|
||||
"total_deleted": int(df.iloc[0]["total_deleted"] or 0),
|
||||
}
|
||||
except Exception as e:
|
||||
print(f"[SyncLogManager] Error getting sync summary: {e}")
|
||||
|
||||
return {
|
||||
"total_syncs": 0,
|
||||
"success_count": 0,
|
||||
"failed_count": 0,
|
||||
"partial_count": 0,
|
||||
"total_inserted": 0,
|
||||
"total_updated": 0,
|
||||
"total_deleted": 0,
|
||||
}
|
||||
|
||||
|
||||
# 便捷函数
|
||||
|
||||
|
||||
def log_sync_start(
|
||||
table_name: str,
|
||||
sync_type: str,
|
||||
date_range_start: Optional[str] = None,
|
||||
date_range_end: Optional[str] = None,
|
||||
metadata: Optional[Dict[str, Any]] = None,
|
||||
) -> None:
|
||||
"""便捷函数：记录同步开始。
|
||||
|
||||
Args:
|
||||
table_name: 表名
|
||||
sync_type: 同步类型
|
||||
date_range_start: 日期范围起始
|
||||
date_range_end: 日期范围结束
|
||||
metadata: 元数据
|
||||
"""
|
||||
manager = SyncLogManager()
|
||||
manager.start_sync(
|
||||
table_name, sync_type, date_range_start, date_range_end, metadata
|
||||
)
|
||||
|
||||
|
||||
def log_sync_complete(
|
||||
table_name: str,
|
||||
status: str = "success",
|
||||
records_inserted: int = 0,
|
||||
records_updated: int = 0,
|
||||
records_deleted: int = 0,
|
||||
error_message: Optional[str] = None,
|
||||
sync_type: str = "incremental",
|
||||
) -> None:
|
||||
"""便捷函数：记录同步完成。
|
||||
|
||||
Args:
|
||||
table_name: 表名
|
||||
status: 状态
|
||||
records_inserted: 插入数
|
||||
records_updated: 更新数
|
||||
records_deleted: 删除数
|
||||
error_message: 错误信息
|
||||
sync_type: 同步类型
|
||||
"""
|
||||
manager = SyncLogManager()
|
||||
manager.complete_sync(
|
||||
table_name,
|
||||
status,
|
||||
records_inserted,
|
||||
records_updated,
|
||||
records_deleted,
|
||||
error_message,
|
||||
sync_type,
|
||||
)
|
||||
@@ -101,14 +101,14 @@ EXCLUDED_FACTORS = [
|
||||
'GTJA_alpha005',
|
||||
'GTJA_alpha036',
|
||||
'GTJA_alpha027',
|
||||
'GTJA_alpha053',
|
||||
'GTJA_alpha044',
|
||||
'GTJA_alpha073',
|
||||
'GTJA_alpha104',
|
||||
'GTJA_alpha103',
|
||||
'GTJA_alpha087',
|
||||
'GTJA_alpha105',
|
||||
'GTJA_alpha092',
|
||||
'GTJA_alpha087',
|
||||
'GTJA_alpha085',
|
||||
'GTJA_alpha044',
|
||||
'GTJA_alpha062',
|
||||
'GTJA_alpha124',
|
||||
'GTJA_alpha133',
|
||||
@@ -203,23 +203,37 @@ print("\n" + "=" * 80)
|
||||
print("开始训练")
|
||||
print("=" * 80)
|
||||
|
||||
# 步骤 1: 股票池筛选
|
||||
print("\n[步骤 1/6] 股票池筛选")
|
||||
# 步骤 1: 应用过滤器（ST股票过滤等）
|
||||
print("\n[步骤 1/7] 应用数据过滤器")
|
||||
print("-" * 60)
|
||||
filtered_data = data
|
||||
if st_filter:
|
||||
print(" 应用 ST 股票过滤器...")
|
||||
data_before = len(filtered_data)
|
||||
filtered_data = st_filter.filter(filtered_data)
|
||||
data_after = len(filtered_data)
|
||||
print(f" 过滤前记录数: {data_before}")
|
||||
print(f" 过滤后记录数: {data_after}")
|
||||
print(f" 删除 ST 股票记录数: {data_before - data_after}")
|
||||
else:
|
||||
print(" 未配置 ST 过滤器，跳过")
|
||||
|
||||
# 步骤 2: 股票池筛选
|
||||
print("\n[步骤 2/7] 股票池筛选")
|
||||
print("-" * 60)
|
||||
if pool_manager:
|
||||
print(" 执行每日独立筛选股票池...")
|
||||
filtered_data = pool_manager.filter_and_select_daily(data)
|
||||
print(f" 筛选前数据规模: {data.shape}")
|
||||
print(f" 筛选后数据规模: {filtered_data.shape}")
|
||||
print(f" 筛选前股票数: {data['ts_code'].n_unique()}")
|
||||
print(f" 筛选后股票数: {filtered_data['ts_code'].n_unique()}")
|
||||
print(f" 删除记录数: {len(data) - len(filtered_data)}")
|
||||
pool_data_before = len(filtered_data)
|
||||
filtered_data = pool_manager.filter_and_select_daily(filtered_data)
|
||||
pool_data_after = len(filtered_data)
|
||||
print(f" 筛选前数据规模: {pool_data_before}")
|
||||
print(f" 筛选后数据规模: {pool_data_after}")
|
||||
print(f" 删除记录数: {pool_data_before - pool_data_after}")
|
||||
else:
|
||||
filtered_data = data
|
||||
print(" 未配置股票池管理器，跳过筛选")
|
||||
# %%
|
||||
# 步骤 2: 划分训练/验证/测试集（正确的三分法）
|
||||
print("\n[步骤 2/6] 划分训练集、验证集和测试集")
|
||||
# 步骤 3: 划分训练/验证/测试集（正确的三分法）
|
||||
print("\n[步骤 3/7] 划分训练集、验证集和测试集")
|
||||
print("-" * 60)
|
||||
if splitter:
|
||||
# 正确的三分法：train用于训练，val用于验证/早停，test仅用于最终评估
|
||||
@@ -251,8 +265,8 @@ else:
|
||||
test_data = filtered_data
|
||||
print(" 未配置划分器，全部作为训练集")
|
||||
# %%
|
||||
# 步骤 3: 数据质量检查（必须在预处理之前）
|
||||
print("\n[步骤 3/7] 数据质量检查")
|
||||
# 步骤 4: 数据质量检查（必须在预处理之前）
|
||||
print("\n[步骤 4/7] 数据质量检查")
|
||||
print("-" * 60)
|
||||
print(" [说明] 此检查在 fillna 等处理之前执行，用于发现数据问题")
|
||||
|
||||
@@ -269,8 +283,8 @@ check_data_quality(test_data, feature_cols, raise_on_error=True)
|
||||
print(" [成功] 数据质量检查通过，未发现异常")
|
||||
|
||||
# %%
|
||||
# 步骤 4: 训练集数据处理
|
||||
print("\n[步骤 4/7] 训练集数据处理")
|
||||
# 步骤 5: 训练集数据处理
|
||||
print("\n[步骤 5/7] 训练集数据处理")
|
||||
print("-" * 60)
|
||||
fitted_processors = []
|
||||
if processors:
|
||||
@@ -296,7 +310,7 @@ for col in feature_cols[:5]: # 只显示前5个特征的缺失值
|
||||
if null_count > 0:
|
||||
print(f" {col}: {null_count} ({null_count / len(train_data) * 100:.2f}%)")
|
||||
# %%
|
||||
# 步骤 4: 训练模型
|
||||
# 步骤 5: 训练模型
|
||||
print("\n[步骤 5/7] 训练模型")
|
||||
print("-" * 60)
|
||||
print(f" 模型类型: LightGBM")
|
||||
@@ -318,7 +332,7 @@ print("\n 开始训练...")
|
||||
model.fit(X_train, y_train)
|
||||
print(" 训练完成！")
|
||||
# %%
|
||||
# 步骤 5: 测试集数据处理
|
||||
# 步骤 6: 测试集数据处理
|
||||
print("\n[步骤 6/7] 测试集数据处理")
|
||||
print("-" * 60)
|
||||
if processors and test_data is not train_data:
|
||||
@@ -334,7 +348,7 @@ if processors and test_data is not train_data:
|
||||
else:
|
||||
print(" 跳过测试集处理")
|
||||
# %%
|
||||
# 步骤 6: 生成预测
|
||||
# 步骤 7: 生成预测
|
||||
print("\n[步骤 7/7] 生成预测")
|
||||
print("-" * 60)
|
||||
X_test = test_data.select(feature_cols)
|
||||
|
||||
403
tests/test_sync_transaction_and_logs.py
Normal file
403
tests/test_sync_transaction_and_logs.py
Normal file
@@ -0,0 +1,403 @@
|
||||
"""测试同步事务和日志功能。
|
||||
|
||||
测试内容:
|
||||
1. 事务支持 - BEGIN/COMMIT/ROLLBACK
|
||||
2. 同步日志记录 - SyncLogManager
|
||||
3. ThreadSafeStorage 事务批量写入
|
||||
"""
|
||||
|
||||
import pytest
|
||||
import pandas as pd
|
||||
import os
|
||||
import tempfile
|
||||
from datetime import datetime, timedelta
|
||||
from pathlib import Path
|
||||
|
||||
# 设置测试环境变量
|
||||
os.environ["DATA_PATH"] = tempfile.mkdtemp()
|
||||
os.environ["TUSHARE_TOKEN"] = "test_token"
|
||||
|
||||
from src.data.storage import Storage, ThreadSafeStorage
|
||||
from src.data.sync_logger import SyncLogManager, SyncLogEntry
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def temp_storage():
|
||||
"""创建临时存储实例用于测试。"""
|
||||
# 使用临时目录
|
||||
temp_dir = tempfile.mkdtemp()
|
||||
os.environ["DATA_PATH"] = temp_dir
|
||||
|
||||
# 重置 Storage 单例
|
||||
Storage._instance = None
|
||||
Storage._connection = None
|
||||
|
||||
storage = Storage(read_only=False)
|
||||
yield storage
|
||||
|
||||
# 清理
|
||||
storage.close()
|
||||
Storage._instance = None
|
||||
Storage._connection = None
|
||||
|
||||
|
||||
class TestTransactionSupport:
|
||||
"""测试 Storage 事务支持。"""
|
||||
|
||||
def test_begin_commit_transaction(self, temp_storage):
|
||||
"""测试事务开始和提交。"""
|
||||
# 创建测试表
|
||||
temp_storage._connection.execute("""
|
||||
CREATE TABLE test_table (id INTEGER PRIMARY KEY, value VARCHAR(50))
|
||||
""")
|
||||
|
||||
# 开始事务
|
||||
temp_storage.begin_transaction()
|
||||
|
||||
# 插入数据
|
||||
temp_storage._connection.execute(
|
||||
"INSERT INTO test_table VALUES (1, 'test1'), (2, 'test2')"
|
||||
)
|
||||
|
||||
# 提交事务
|
||||
temp_storage.commit_transaction()
|
||||
|
||||
# 验证数据已提交
|
||||
result = temp_storage._connection.execute(
|
||||
"SELECT COUNT(*) FROM test_table"
|
||||
).fetchone()
|
||||
assert result[0] == 2
|
||||
|
||||
def test_rollback_transaction(self, temp_storage):
|
||||
"""测试事务回滚。"""
|
||||
# 创建测试表并插入初始数据
|
||||
temp_storage._connection.execute("""
|
||||
CREATE TABLE test_table2 (id INTEGER PRIMARY KEY, value VARCHAR(50))
|
||||
""")
|
||||
temp_storage._connection.execute(
|
||||
"INSERT INTO test_table2 VALUES (1, 'initial')"
|
||||
)
|
||||
|
||||
# 开始事务并插入更多数据
|
||||
temp_storage.begin_transaction()
|
||||
temp_storage._connection.execute("INSERT INTO test_table2 VALUES (2, 'temp')")
|
||||
|
||||
# 回滚事务
|
||||
temp_storage.rollback_transaction()
|
||||
|
||||
# 验证临时数据未提交
|
||||
result = temp_storage._connection.execute(
|
||||
"SELECT COUNT(*) FROM test_table2"
|
||||
).fetchone()
|
||||
assert result[0] == 1
|
||||
|
||||
def test_transaction_context_manager(self, temp_storage):
|
||||
"""测试事务上下文管理器。"""
|
||||
# 创建测试表
|
||||
temp_storage._connection.execute("""
|
||||
CREATE TABLE test_table3 (id INTEGER PRIMARY KEY, value VARCHAR(50))
|
||||
""")
|
||||
|
||||
# 使用上下文管理器（正常完成）
|
||||
with temp_storage.transaction():
|
||||
temp_storage._connection.execute(
|
||||
"INSERT INTO test_table3 VALUES (1, 'committed')"
|
||||
)
|
||||
|
||||
# 验证数据已提交
|
||||
result = temp_storage._connection.execute(
|
||||
"SELECT COUNT(*) FROM test_table3"
|
||||
).fetchone()
|
||||
assert result[0] == 1
|
||||
|
||||
def test_transaction_context_manager_rollback(self, temp_storage):
|
||||
"""测试事务上下文管理器异常回滚。"""
|
||||
# 创建测试表
|
||||
temp_storage._connection.execute("""
|
||||
CREATE TABLE test_table4 (id INTEGER PRIMARY KEY, value VARCHAR(50))
|
||||
""")
|
||||
|
||||
# 使用上下文管理器（发生异常）
|
||||
try:
|
||||
with temp_storage.transaction():
|
||||
temp_storage._connection.execute(
|
||||
"INSERT INTO test_table4 VALUES (1, 'temp')"
|
||||
)
|
||||
raise ValueError("Test error")
|
||||
except ValueError:
|
||||
pass
|
||||
|
||||
# 验证数据未提交
|
||||
result = temp_storage._connection.execute(
|
||||
"SELECT COUNT(*) FROM test_table4"
|
||||
).fetchone()
|
||||
assert result[0] == 0
|
||||
|
||||
|
||||
class TestSyncLogManager:
|
||||
"""测试同步日志管理器。"""
|
||||
|
||||
def test_log_table_creation(self, temp_storage):
|
||||
"""测试日志表自动创建。"""
|
||||
# 创建日志管理器会自动创建表
|
||||
log_manager = SyncLogManager(temp_storage)
|
||||
|
||||
# 验证表存在
|
||||
result = temp_storage._connection.execute("""
|
||||
SELECT COUNT(*) FROM information_schema.tables
|
||||
WHERE table_name = '_sync_logs'
|
||||
""").fetchone()
|
||||
assert result[0] == 1
|
||||
|
||||
def test_start_sync(self, temp_storage):
|
||||
"""测试开始记录同步。"""
|
||||
log_manager = SyncLogManager(temp_storage)
|
||||
|
||||
# 记录同步开始
|
||||
entry = log_manager.start_sync(
|
||||
table_name="test_table",
|
||||
sync_type="incremental",
|
||||
date_range_start="20240101",
|
||||
date_range_end="20240131",
|
||||
metadata={"test": True},
|
||||
)
|
||||
|
||||
assert entry.table_name == "test_table"
|
||||
assert entry.sync_type == "incremental"
|
||||
assert entry.status == "running"
|
||||
assert entry.date_range_start == "20240101"
|
||||
|
||||
def test_complete_sync(self, temp_storage):
|
||||
"""测试完成同步记录。"""
|
||||
log_manager = SyncLogManager(temp_storage)
|
||||
|
||||
# 开始同步
|
||||
entry = log_manager.start_sync(table_name="test_table", sync_type="full")
|
||||
|
||||
# 完成同步
|
||||
log_manager.complete_sync(
|
||||
entry,
|
||||
status="success",
|
||||
records_inserted=1000,
|
||||
records_updated=100,
|
||||
records_deleted=10,
|
||||
)
|
||||
|
||||
assert entry.status == "success"
|
||||
assert entry.records_inserted == 1000
|
||||
assert entry.records_updated == 100
|
||||
assert entry.records_deleted == 10
|
||||
assert entry.end_time is not None
|
||||
|
||||
def test_complete_sync_with_error(self, temp_storage):
|
||||
"""测试失败同步记录。"""
|
||||
log_manager = SyncLogManager(temp_storage)
|
||||
|
||||
entry = log_manager.start_sync(table_name="test_table", sync_type="incremental")
|
||||
|
||||
log_manager.complete_sync(
|
||||
entry, status="failed", error_message="Connection timeout"
|
||||
)
|
||||
|
||||
assert entry.status == "failed"
|
||||
assert entry.error_message == "Connection timeout"
|
||||
|
||||
def test_get_sync_history(self, temp_storage):
|
||||
"""测试查询同步历史。"""
|
||||
log_manager = SyncLogManager(temp_storage)
|
||||
|
||||
# 创建几条记录
|
||||
for i in range(3):
|
||||
entry = log_manager.start_sync(
|
||||
table_name="test_table", sync_type="incremental"
|
||||
)
|
||||
log_manager.complete_sync(entry, status="success", records_inserted=100)
|
||||
|
||||
# 查询历史
|
||||
history = log_manager.get_sync_history(table_name="test_table", limit=10)
|
||||
|
||||
assert len(history) == 3
|
||||
assert all(h["table_name"] == "test_table" for _, h in history.iterrows())
|
||||
|
||||
def test_get_last_sync(self, temp_storage):
|
||||
"""测试获取最近同步记录。"""
|
||||
log_manager = SyncLogManager(temp_storage)
|
||||
|
||||
# 创建两条记录
|
||||
entry1 = log_manager.start_sync(table_name="table1", sync_type="full")
|
||||
log_manager.complete_sync(entry1, status="success")
|
||||
|
||||
entry2 = log_manager.start_sync(table_name="table1", sync_type="incremental")
|
||||
log_manager.complete_sync(entry2, status="success")
|
||||
|
||||
# 获取最近一次
|
||||
last_sync = log_manager.get_last_sync("table1")
|
||||
|
||||
assert last_sync is not None
|
||||
assert last_sync["sync_type"] == "incremental"
|
||||
|
||||
def test_get_sync_summary(self, temp_storage):
|
||||
"""测试获取同步汇总统计。"""
|
||||
log_manager = SyncLogManager(temp_storage)
|
||||
|
||||
# 创建多条记录
|
||||
for i in range(5):
|
||||
entry = log_manager.start_sync(
|
||||
table_name="test_table", sync_type="incremental"
|
||||
)
|
||||
log_manager.complete_sync(entry, status="success", records_inserted=100)
|
||||
|
||||
# 添加一条失败记录
|
||||
entry = log_manager.start_sync(table_name="test_table", sync_type="full")
|
||||
log_manager.complete_sync(entry, status="failed", error_message="error")
|
||||
|
||||
# 获取汇总
|
||||
summary = log_manager.get_sync_summary("test_table", days=30)
|
||||
|
||||
assert summary["total_syncs"] == 6
|
||||
assert summary["success_count"] == 5
|
||||
assert summary["failed_count"] == 1
|
||||
assert summary["total_inserted"] == 500
|
||||
|
||||
|
||||
class TestThreadSafeStorageTransaction:
|
||||
"""测试 ThreadSafeStorage 事务支持。"""
|
||||
|
||||
def test_flush_with_transaction(self, temp_storage):
|
||||
"""测试带事务的批量写入。"""
|
||||
# 重置 Storage 单例
|
||||
Storage._instance = None
|
||||
Storage._connection = None
|
||||
|
||||
ts_storage = ThreadSafeStorage()
|
||||
|
||||
# 创建测试表
|
||||
ts_storage.storage._connection.execute("""
|
||||
CREATE TABLE test_data (ts_code VARCHAR(16), trade_date DATE, value DOUBLE)
|
||||
""")
|
||||
|
||||
# 准备测试数据
|
||||
df1 = pd.DataFrame(
|
||||
{
|
||||
"ts_code": ["000001.SZ", "000002.SZ"],
|
||||
"trade_date": ["20240101", "20240101"],
|
||||
"value": [100.0, 200.0],
|
||||
}
|
||||
)
|
||||
|
||||
df2 = pd.DataFrame(
|
||||
{
|
||||
"ts_code": ["000003.SZ", "000004.SZ"],
|
||||
"trade_date": ["20240102", "20240102"],
|
||||
"value": [300.0, 400.0],
|
||||
}
|
||||
)
|
||||
|
||||
# 加入队列
|
||||
ts_storage.queue_save("test_data", df1)
|
||||
ts_storage.queue_save("test_data", df2)
|
||||
|
||||
# 使用事务刷新
|
||||
ts_storage.flush(use_transaction=True)
|
||||
|
||||
# 验证数据
|
||||
result = ts_storage.storage._connection.execute(
|
||||
"SELECT COUNT(*) FROM test_data"
|
||||
).fetchone()
|
||||
assert result[0] == 4
|
||||
|
||||
def test_flush_rollback_on_error(self, temp_storage):
|
||||
"""测试错误时回滚。"""
|
||||
# 这个测试比较复杂，需要模拟错误情况
|
||||
# 简化版本：验证错误不会导致数据不一致
|
||||
Storage._instance = None
|
||||
Storage._connection = None
|
||||
|
||||
ts_storage = ThreadSafeStorage()
|
||||
|
||||
# 创建测试表（使用唯一表名）
|
||||
ts_storage.storage._connection.execute("""
|
||||
CREATE TABLE test_data2 (ts_code VARCHAR(16) PRIMARY KEY, value DOUBLE)
|
||||
""")
|
||||
|
||||
# 插入初始数据
|
||||
df = pd.DataFrame({"ts_code": ["000001.SZ"], "value": [100.0]})
|
||||
ts_storage.queue_save("test_data2", df, use_upsert=False)
|
||||
ts_storage.flush(use_transaction=True)
|
||||
|
||||
# 验证
|
||||
result = ts_storage.storage._connection.execute(
|
||||
"SELECT COUNT(*) FROM test_data2"
|
||||
).fetchone()
|
||||
assert result[0] == 1
|
||||
|
||||
|
||||
class TestIntegration:
|
||||
"""集成测试。"""
|
||||
|
||||
def test_full_sync_workflow(self, temp_storage):
|
||||
"""测试完整同步工作流。"""
|
||||
# 1. 初始化日志管理器
|
||||
log_manager = SyncLogManager(temp_storage)
|
||||
|
||||
# 2. 创建测试表
|
||||
temp_storage._connection.execute("""
|
||||
CREATE TABLE sync_test_table (
|
||||
ts_code VARCHAR(16),
|
||||
trade_date DATE,
|
||||
value DOUBLE,
|
||||
PRIMARY KEY (ts_code, trade_date)
|
||||
)
|
||||
""")
|
||||
|
||||
# 3. 开始同步
|
||||
log_entry = log_manager.start_sync(
|
||||
table_name="sync_test_table",
|
||||
sync_type="full",
|
||||
date_range_start="20240101",
|
||||
date_range_end="20240131",
|
||||
)
|
||||
|
||||
# 4. 在事务中执行同步
|
||||
temp_storage.begin_transaction()
|
||||
try:
|
||||
# 模拟同步：插入数据
|
||||
df = pd.DataFrame(
|
||||
{
|
||||
"ts_code": ["000001.SZ", "000002.SZ"],
|
||||
"trade_date": ["20240115", "20240115"],
|
||||
"value": [100.0, 200.0],
|
||||
}
|
||||
)
|
||||
|
||||
# 转换日期格式
|
||||
df["trade_date"] = pd.to_datetime(df["trade_date"], format="%Y%m%d").dt.date
|
||||
|
||||
# 使用 storage.save
|
||||
temp_storage.save("sync_test_table", df, mode="append")
|
||||
|
||||
# 提交事务
|
||||
temp_storage.commit_transaction()
|
||||
|
||||
# 5. 记录成功
|
||||
log_manager.complete_sync(
|
||||
log_entry, status="success", records_inserted=len(df)
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
temp_storage.rollback_transaction()
|
||||
log_manager.complete_sync(log_entry, status="failed", error_message=str(e))
|
||||
raise
|
||||
|
||||
# 6. 验证
|
||||
assert log_entry.status == "success"
|
||||
assert log_entry.records_inserted == 2
|
||||
|
||||
# 7. 查询日志历史
|
||||
history = log_manager.get_sync_history(table_name="sync_test_table")
|
||||
assert len(history) == 1
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# 运行测试
|
||||
pytest.main([__file__, "-v"])
|
||||
Reference in New Issue
Block a user