267 lines
10 KiB
Python
267 lines
10 KiB
Python
import pyodbc
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from config import SQL_SERVER_CONN, ACCESS_DRIVER, SYNC_MAPPING, BATCH_SIZE
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import db_utils
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import time
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import os
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import ntfy_utils
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from log_utils import (LoggerManager, log_success, log_error, log_warning, log_info, log_processing,
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log_skip, log_start, log_file, log_database, log_sync, log_complete)
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# 初始化日志管理器
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LoggerManager("init_full_sync", log_prefix="full_sync")
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def format_duration(seconds):
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"""格式化时长显示"""
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if seconds < 60:
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return f"{seconds:.1f}秒"
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elif seconds < 3600:
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return f"{seconds/60:.1f}分钟"
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else:
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return f"{seconds/3600:.1f}小时"
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def has_identity_column(sql_cursor, schema, table):
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"""检查表是否包含标识列"""
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query = """
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SELECT COUNT(*)
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FROM sys.columns c
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JOIN sys.tables t ON c.object_id = t.object_id
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JOIN sys.schemas s ON t.schema_id = s.schema_id
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WHERE s.name = ? AND t.name = ? AND c.is_identity = 1
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"""
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sql_cursor.execute(query, (schema, table))
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return sql_cursor.fetchone()[0] > 0
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def _send_summary_notification(sync_results, success_count, failed_count, total_rows, total_time):
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"""发送汇总 ntfy 通知"""
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if not sync_results:
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return
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# 分类成功和失败的表
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success_tables = [r for r in sync_results if r['status'] == 'success']
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failed_tables = [r for r in sync_results if r['status'] == 'failed']
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# 构建消息
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lines = []
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lines.append("🎯 全量同步完成\n")
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# 成功的表
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if success_tables:
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lines.append(f"✅ 成功 {len(success_tables)} 张表:")
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for r in success_tables:
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lines.append(f" • {r['table']}: {r['rows']:,} 行, {format_duration(r['duration'])}")
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lines.append("")
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# 失败的表
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if failed_tables:
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lines.append(f"❌ 失败 {failed_count} 张表:")
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for r in failed_tables:
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error_brief = r['error'][:50] + "..." if len(r['error']) > 50 else r['error']
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lines.append(f" • {r['table']}: {error_brief}")
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lines.append("")
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# 总计
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lines.append(f"总计: {total_rows:,} 行 | 用时: {format_duration(total_time)}")
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message = "\n".join(lines)
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# 根据成功/失败情况决定优先级和标签
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if failed_count > 0:
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priority = "high"
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tags = ["warning", "database"]
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else:
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priority = "default"
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tags = ["white_check_mark", "database"]
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ntfy_utils.send_ntfy(
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message=message,
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title="全量同步完成",
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priority=priority,
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tags=tags
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)
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def run_full_sync():
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log_info("=" * 70)
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log_start( "全量初始化同步")
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log_info( f"配置文件数: {len(SYNC_MAPPING)} 个")
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log_info( f"批次大小: {BATCH_SIZE} 行")
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log_info("=" * 70)
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sync_start_time = time.time()
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total_tables = 0
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success_tables = 0
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failed_tables = 0
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total_rows = 0
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# 收集每张表的同步结果，用于最终汇总通知
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sync_results = [] # 格式: {'table': str, 'status': 'success'|'failed', 'rows': int, 'duration': float, 'error': str}
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try:
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sql_conn = db_utils.get_sql_conn()
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sql_cursor = sql_conn.cursor()
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sql_cursor.fast_executemany = True
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log_database( "SQL Server 连接成功")
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except Exception as e:
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log_error( f"SQL Server 连接失败: {e}")
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return
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# 第一层循环:遍历配置文件中的所有文件路径
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for acc_path, tables_map in SYNC_MAPPING.items():
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if not os.path.exists(acc_path):
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log_skip( f"文件不存在: {acc_path}")
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continue
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log_file( f"开始处理: {os.path.basename(acc_path)}")
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file_start_time = time.time()
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file_success = 0
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file_failed = 0
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file_rows = 0
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try:
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acc_conn = db_utils.get_access_conn(acc_path)
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acc_cursor = acc_conn.cursor()
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log_database( f"Access 文件连接成功: {os.path.basename(acc_path)}")
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# 第二层循环:遍历该文件下的所有表映射
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for acc_table, target_config in tables_map.items():
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total_tables += 1
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target_schema = target_config['target_schema']
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target_table = target_config['target_table']
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full_target_name = db_utils.fmt_table(target_schema, target_table)
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log_processing( f"表 [{acc_table}] → [{target_table}]")
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table_start_time = time.time()
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try:
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# 1. 检查 Access 表是否存在
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acc_cursor.execute(f"SELECT TOP 1 * FROM [{acc_table}]")
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# 2. 获取列结构
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columns = [col[0] for col in acc_cursor.description]
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log_info( f" 检测到 {len(columns)} 个列")
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insert_sql = db_utils.generate_insert_sql(target_schema, target_table, columns)
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# 3. TRUNCATE 目标表
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sql_cursor.execute(f"TRUNCATE TABLE {full_target_name}")
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log_info( f" 已清空目标表")
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# 4. 检查并启用 IDENTITY_INSERT
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has_identity = has_identity_column(sql_cursor, target_schema, target_table)
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identity_enabled = False
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if has_identity:
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try:
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sql_cursor.execute(f"SET IDENTITY_INSERT {full_target_name} ON")
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identity_enabled = True
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log_info( f" 已启用 IDENTITY_INSERT")
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except Exception as id_err:
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log_error( f" 无法启用 IDENTITY_INSERT: {id_err}")
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raise
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# 5. 传输数据
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log_info( f" 开始数据传输...")
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acc_cursor.execute(f"SELECT * FROM [{acc_table}]")
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table_rows = 0
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start_time = time.time()
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last_log_time = start_time
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while True:
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rows = acc_cursor.fetchmany(BATCH_SIZE)
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if not rows: break
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sql_cursor.executemany(insert_sql, rows)
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table_rows += len(rows)
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# 每5秒或每10000行记录一次进度
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current_time = time.time()
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if (current_time - last_log_time >= 5) or (table_rows % 10000 == 0):
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elapsed = current_time - start_time
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rate = table_rows / elapsed if elapsed > 0 else 0
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log_info( f" 进度: {table_rows:,} 行 | 速率: {rate:,.0f} 行/秒")
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last_log_time = current_time
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# 6. 关闭 IDENTITY_INSERT
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if identity_enabled:
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try:
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sql_cursor.execute(f"SET IDENTITY_INSERT {full_target_name} OFF")
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log_info( f" 已关闭 IDENTITY_INSERT")
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except Exception as id_err:
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log_warning( f" 关闭 IDENTITY_INSERT 时警告: {id_err}")
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sql_conn.commit()
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# 显示最终统计
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table_time = time.time() - table_start_time
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final_rate = table_rows / table_time if table_time > 0 else 0
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log_info( f"表 [{target_table}] 完成: {table_rows:,} 行 | 速率: {final_rate:,.0f} 行/秒 | 用时: {format_duration(table_time)}")
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# 收集成功结果
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sync_results.append({
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'table': target_table,
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'status': 'success',
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'rows': table_rows,
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'duration': table_time,
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'error': None
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})
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success_tables += 1
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file_success += 1
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total_rows += table_rows
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file_rows += table_rows
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except Exception as tbl_err:
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failed_tables += 1
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file_failed += 1
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error_msg = str(tbl_err)
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log_info( f"表 [{acc_table}] 同步失败: {error_msg}")
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# 收集失败结果
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sync_results.append({
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'table': target_table,
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'status': 'failed',
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'rows': 0,
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'duration': time.time() - table_start_time,
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'error': error_msg
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})
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sql_conn.rollback()
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# 确保清理 IDENTITY_INSERT 状态
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try:
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sql_cursor.execute(f"SET IDENTITY_INSERT {full_target_name} OFF")
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except:
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pass
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acc_conn.close()
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# 文件级别汇总
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file_time = time.time() - file_start_time
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summary = f"文件 [{os.path.basename(acc_path)}] 完成: "
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summary += f"成功 {file_success} 张表"
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if file_failed > 0:
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summary += f" | 失败 {file_failed} 张表"
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summary += f" | 共 {file_rows:,} 行 | 用时: {format_duration(file_time)}"
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log_sync( summary)
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except Exception as file_err:
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log_error( f"文件 [{os.path.basename(acc_path)}] 处理失败: {file_err}", exc_info=True)
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sql_conn.close()
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# 总结统计
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sync_time = time.time() - sync_start_time
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log_info("\n" + "=" * 70)
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log_info( "全量同步任务结束")
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log_info("-" * 70)
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log_info( f"总表数: {total_tables} 张 | 成功: {success_tables} 张 | 失败: {failed_tables} 张")
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log_info( f"总行数: {total_rows:,} 行")
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log_info( f"总用时: {format_duration(sync_time)}")
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if total_rows > 0 and sync_time > 0:
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log_info( f"整体平均速率: {total_rows/sync_time:,.0f} 行/秒")
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log_info("=" * 70)
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# 发送汇总 ntfy 通知
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_send_summary_notification(sync_results, success_tables, failed_tables, total_rows, sync_time)
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if __name__ == "__main__":
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run_full_sync() |