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Enhance logging and synchronization features across multiple scripts

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- Added detailed logging functionality to init_full_sync.py and run_incremental_sync.py for better tracking of synchronization processes.
- Updated configuration mappings in config.py to include additional Access database tables.
- Improved error handling and user feedback in vbareplace.py, including the ability to refresh linked tables in Access.
- Adjusted polling intervals and batch sizes for performance optimization.
This commit is contained in:
Misaka_Company
2026-01-07 15:01:27 +08:00
parent 77b72392a3
commit a1c8a572bd
4 changed files with 555 additions and 155 deletions
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293
config.py
View File

@@ -40,19 +40,290 @@ SYNC_MAPPING = {
"target_schema": "productionContractData",
"target_table": "26年温度计合同数据",
"pk_col": "ID"
},
"25年压力表合同数据": {
"target_schema": "productionContractData",
"target_table": "25年压力表合同数据",
"pk_col": "ID"
},
"25年温度计合同数据": {
"target_schema": "productionContractData",
"target_table": "25年温度计合同数据",
"pk_col": "ID"
}
},
r"\\192.168.110.114\生产进度表\2026年数据\成品入库.accdb": {
"成品交检记录": {
"target_schema": "productWarehousing",
"target_table": "成品交检记录_YEAR2026",
"pk_col": "ID"
},
"成品入库记录": {
"target_schema": "productWarehousing",
"target_table": "成品入库记录_YEAR2026",
"pk_col": "ID"
}
},
# # 第二个 Access 文件 (可能有同名的 UserInfo 表)
# r"D:\Data\ProjectB\backup.mdb": {
# "UserInfo": {
# "target_schema": "dbo",
# "target_table": "ProjB_UserInfo", # 映射到 B 表
# "pk_col": "ID"
# }
# }
r"\\192.168.110.114\生产进度表\2026年数据\一车间.accdb": {
"一车间记录": {
"target_schema": "workshopOne",
"target_table": "一车间记录_YEAR2026",
"pk_col": "ID"
}
},
r"\\192.168.110.114\生产进度表\2026年数据\二车间.accdb": {
"二车间记录": {
"target_schema": "workshopTwo",
"target_table": "二车间记录_YEAR2026",
"pk_col": "ID"
}
},
r"\\192.168.110.114\生产进度表\2026年数据\三车间.accdb": {
"三车间记录": {
"target_schema": "workshopThree",
"target_table": "三车间记录_YEAR2026",
"pk_col": "ID"
},
"温度计调校记录": {
"target_schema": "workshopThree",
"target_table": "温度计调校记录_YEAR2026",
"pk_col": "ID"
}
},
r"\\192.168.110.114\生产进度表\2026年数据\机加工.accdb": {
"隔膜机加接收": {
"target_schema": "machining",
"target_table": "隔膜机加接收_YEAR2026",
"pk_col": "ID"
},
"膜片焊接": {
"target_schema": "machining",
"target_table": "膜片焊接_YEAR2026",
"pk_col": "ID"
},
"膜片接收": {
"target_schema": "machining",
"target_table": "膜片接收_YEAR2026",
"pk_col": "ID"
},
"喷涂寄出": {
"target_schema": "machining",
"target_table": "喷涂寄出_YEAR2026",
"pk_col": "ID"
}
},
r"\\192.168.110.114\生产进度表\2026年数据\计划.accdb": {
"报警器接单记录": {
"target_schema": "contractPlanning",
"target_table": "报警器接单记录_YEAR2026",
"pk_col": "ID"
},
"二车间接单记录": {
"target_schema": "contractPlanning",
"target_table": "二车间接单记录_YEAR2026",
"pk_col": "ID"
},
"隔膜接单记录": {
"target_schema": "contractPlanning",
"target_table": "隔膜接单记录_YEAR2026",
"pk_col": "ID"
},
"过压保护器接单记录": {
"target_schema": "contractPlanning",
"target_table": "过压保护器接单记录_YEAR2026",
"pk_col": "ID"
},
"精密表部件接收记录": {
"target_schema": "contractPlanning",
"target_table": "精密表部件接收记录_YEAR2026",
"pk_col": "ID"
},
"精密表接单记录": {
"target_schema": "contractPlanning",
"target_table": "精密表接单记录_YEAR2026",
"pk_col": "ID"
},
"库房接单记录": {
"target_schema": "contractPlanning",
"target_table": "库房接单记录_YEAR2026",
"pk_col": "ID"
},
"软管接单记录": {
"target_schema": "contractPlanning",
"target_table": "软管接单记录_YEAR2026",
"pk_col": "ID"
},
"氩弧焊接单记录": {
"target_schema": "contractPlanning",
"target_table": "氩弧焊接单记录_YEAR2026",
"pk_col": "ID"
},
"一车间接单记录": {
"target_schema": "contractPlanning",
"target_table": "一车间接单记录_YEAR2026",
"pk_col": "ID"
},
"阻尼器接单记录": {
"target_schema": "contractPlanning",
"target_table": "阻尼器接单记录_YEAR2026",
"pk_col": "ID"
}
},
r"\\192.168.110.114\生产进度表\2026年数据\检验记录数据库.accdb": {
"检验合格记录表": {
"target_schema": "inspectionRecords",
"target_table": "检验合格记录表_YEAR2026",
"pk_col": "ID"
}
},
r"\\192.168.110.114\生产进度表\2026年数据\零件库.accdb": {
"表盘缺件记录": {
"target_schema": "partsWarehouse",
"target_table": "表盘缺件记录_YEAR2026",
"pk_col": "ID"
},
"表盘入库记录": {
"target_schema": "partsWarehouse",
"target_table": "表盘入库记录_YEAR2026",
"pk_col": "ID"
},
"部件发放记录": {
"target_schema": "partsWarehouse",
"target_table": "部件发放记录_YEAR2026",
"pk_col": "ID"
},
"出库单发出记录": {
"target_schema": "partsWarehouse",
"target_table": "出库单发出记录_YEAR2026",
"pk_col": "ID"
},
"出库单记录": {
"target_schema": "partsWarehouse",
"target_table": "出库单记录_YEAR2026",
"pk_col": "ID"
},
"法兰缺件记录": {
"target_schema": "partsWarehouse",
"target_table": "法兰缺件记录_YEAR2026",
"pk_col": "ID"
},
"法兰入库记录": {
"target_schema": "partsWarehouse",
"target_table": "法兰入库记录_YEAR2026",
"pk_col": "ID"
},
"卡到库房记录": {
"target_schema": "partsWarehouse",
"target_table": "卡到库房记录_YEAR2026",
"pk_col": "ID"
},
"喷涂到厂": {
"target_schema": "partsWarehouse",
"target_table": "喷涂到厂_YEAR2026",
"pk_col": "ID"
},
"缺件记录": {
"target_schema": "partsWarehouse",
"target_table": "缺件记录_YEAR2026",
"pk_col": "ID"
},
"温度计法兰缺件记录": {
"target_schema": "partsWarehouse",
"target_table": "温度计法兰缺件记录_YEAR2026",
"pk_col": "ID"
},
"温度计法兰入库记录": {
"target_schema": "partsWarehouse",
"target_table": "温度计法兰入库记录_YEAR2026",
"pk_col": "ID"
}
},
r"\\192.168.110.114\生产进度表\2026年数据\温度计记录.accdb": {
"采 技 机记录": {
"target_schema": "thermometerRecord",
"target_table": "采 技 机记录_YEAR2026",
"pk_col": "ID"
},
"温度计调校记录": {
"target_schema": "thermometerRecord",
"target_table": "温度计调校记录_YEAR2026",
"pk_col": "ID"
},
"温度计检验记录": {
"target_schema": "thermometerRecord",
"target_table": "温度计检验记录_YEAR2026",
"pk_col": "ID"
},
"温度计组装记录": {
"target_schema": "thermometerRecord",
"target_table": "温度计组装记录_YEAR2026",
"pk_col": "ID"
}
},
r"\\192.168.110.114\生产进度表\2026年数据\锡焊数据.accdb": {
"操作者1完成记录": {
"target_schema": "solderingData",
"target_table": "操作者1完成记录_YEAR2026",
"pk_col": "ID"
},
"操作者2完成记录": {
"target_schema": "solderingData",
"target_table": "操作者2完成记录_YEAR2026",
"pk_col": "ID"
},
"零件到车间记录": {
"target_schema": "solderingData",
"target_table": "零件到车间记录_YEAR2026",
"pk_col": "ID"
}
},
r"\\192.168.110.114\生产进度表\2026年数据\氩弧焊.accdb": {
"表壳焊接记录": {
"target_schema": "TIGWelding",
"target_table": "表壳焊接记录_YEAR2026",
"pk_col": "ID"
},
"超压": {
"target_schema": "TIGWelding",
"target_table": "超压_YEAR2026",
"pk_col": "ID"
},
"氦测": {
"target_schema": "TIGWelding",
"target_table": "氦测_YEAR2026",
"pk_col": "ID"
},
"接收": {
"target_schema": "TIGWelding",
"target_table": "接收_YEAR2026",
"pk_col": "ID"
},
"退火": {
"target_schema": "TIGWelding",
"target_table": "退火_YEAR2026",
"pk_col": "ID"
},
"氩弧焊记录": {
"target_schema": "TIGWelding",
"target_table": "氩弧焊记录_YEAR2026",
"pk_col": "ID"
},
"氩弧焊领料": {
"target_schema": "TIGWelding",
"target_table": "氩弧焊领料_YEAR2026",
"pk_col": "ID"
}
},
r"\\192.168.110.114\生产进度表\2026年数据\执行卡下发记录.accdb": {
"执行卡下发记录": {
"target_schema": "executionCardIssuanceRecord",
"target_table": "执行卡下发记录_YEAR2026",
"pk_col": "ID"
}
}
}
# ================= 运行参数 =================
POLL_INTERVAL = 60 # 轮询间隔(秒)
BATCH_SIZE = 1000 # 批量处理大小
POLL_INTERVAL = 5 # 轮询间隔(秒)
BATCH_SIZE = 10000 # 批量处理大小

155
init_full_sync.py
View File

@@ -1,83 +1,196 @@
# init_full_sync.py
import pyodbc
import config
import db_utils
import time
import os
import logging
from datetime import datetime
def setup_logger():
"""初始化日志配置，每次运行生成独立的日志文件"""
# 创建log目录
log_dir = "log"
if not os.path.exists(log_dir):
os.makedirs(log_dir)
# 生成带时间戳的日志文件名
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
log_file = os.path.join(log_dir, f"full_sync_{timestamp}.log")
# 配置日志格式
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s [%(levelname)s] %(message)s',
datefmt='%Y-%m-%d %H:%M:%S',
handlers=[
logging.FileHandler(log_file, encoding='utf-8'),
logging.StreamHandler() # 同时输出到控制台
]
)
logger = logging.getLogger(__name__)
logger.info(f"日志文件: {log_file}")
return logger
def format_duration(seconds):
"""格式化时长显示"""
if seconds < 60:
return f"{seconds:.1f}秒"
elif seconds < 3600:
return f"{seconds/60:.1f}分钟"
else:
return f"{seconds/3600:.1f}小时"
def has_identity_column(sql_cursor, schema, table):
"""检查表是否包含标识列"""
query = """
SELECT COUNT(*)
FROM sys.columns c
JOIN sys.tables t ON c.object_id = t.object_id
JOIN sys.schemas s ON t.schema_id = s.schema_id
WHERE s.name = ? AND t.name = ? AND c.is_identity = 1
"""
sql_cursor.execute(query, (schema, table))
return sql_cursor.fetchone()[0] > 0
def run_full_sync():
print("=== 开始全量初始化同步 ===")
print("注意：将基于 config.SYNC_MAPPING 中的文件路径进行处理")
logger = setup_logger()
logger.info("=== 开始全量初始化同步 ===")
logger.info("注意:将基于 config.SYNC_MAPPING 中的文件路径进行处理")
sync_start_time = time.time()
total_tables = 0
success_tables = 0
failed_tables = 0
total_rows = 0
try:
sql_conn = db_utils.get_sql_conn()
sql_cursor = sql_conn.cursor()
sql_cursor.fast_executemany = True
logger.info("✓ SQL Server 连接成功")
except Exception as e:
logger.error(f"❌ SQL Server 连接失败: {e}")
return
# 第一层循环：遍历配置文件中的所有文件路径
# 第一层循环:遍历配置文件中的所有文件路径
for acc_path, tables_map in config.SYNC_MAPPING.items():
if not os.path.exists(acc_path):
print(f"⚠️ [跳过] 文件不存在: {acc_path}")
logger.warning(f"⚠️ [跳过] 文件不存在: {acc_path}")
continue
print(f"\n📂 正在处理文件: {acc_path}")
logger.info(f"\n📂 正在处理文件: {acc_path}")
try:
acc_conn = db_utils.get_access_conn(acc_path)
acc_cursor = acc_conn.cursor()
logger.info(f" ✓ Access 文件连接成功")
# 第二层循环：遍历该文件下的所有表映射
# 第二层循环:遍历该文件下的所有表映射
for acc_table, target_config in tables_map.items():
total_tables += 1
target_schema = target_config['target_schema']
target_table = target_config['target_table']
full_target_name = db_utils.fmt_table(target_schema, target_table)
print(f" 👉 同步表: [{acc_table}] -> {full_target_name}")
logger.info(f" 👉 开始同步表: [{acc_table}] -> {full_target_name}")
table_start_time = time.time()
try:
# 1. 检查 Access 表是否存在
acc_cursor.execute(f"SELECT TOP 1 * FROM [{acc_table}]")
logger.info(f" ✓ Access 表 [{acc_table}] 存在")
# 2. 获取列结构
columns = [col[0] for col in acc_cursor.description]
logger.info(f" ✓ 获取到 {len(columns)} 个列: {', '.join(columns)}")
insert_sql = db_utils.generate_insert_sql(target_schema, target_table, columns)
# 3. TRUNCATE 目标表
sql_cursor.execute(f"TRUNCATE TABLE {full_target_name}")
logger.info(f" ✓ 已清空目标表")
# 4. 开启 IDENTITY_INSERT (尝试)
try: sql_cursor.execute(f"SET IDENTITY_INSERT {full_target_name} ON")
except: pass
# 4. 检查并启用 IDENTITY_INSERT
has_identity = has_identity_column(sql_cursor, target_schema, target_table)
identity_enabled = False
if has_identity:
try:
sql_cursor.execute(f"SET IDENTITY_INSERT {full_target_name} ON")
identity_enabled = True
logger.info(f" ✓ 已启用 IDENTITY_INSERT")
except Exception as id_err:
logger.error(f" ⚠️ 无法启用 IDENTITY_INSERT: {id_err}")
raise
# 5. 传输数据
print(f" 正在读取并写入数据...")
logger.info(f" 正在读取并写入数据...")
acc_cursor.execute(f"SELECT * FROM [{acc_table}]")
total_rows = 0
table_rows = 0
start_time = time.time()
while True:
rows = acc_cursor.fetchmany(config.BATCH_SIZE)
if not rows: break
sql_cursor.executemany(insert_sql, rows)
total_rows += len(rows)
print(f" 已写入 {total_rows} 行...", end='\r')
table_rows += len(rows)
# 定期记录进度到日志
if table_rows % (config.BATCH_SIZE * 10) == 0:
elapsed = time.time() - start_time
rate = table_rows / elapsed if elapsed > 0 else 0
logger.info(f" 进度: 已写入 {table_rows:,} 行 | 速率: {rate:,.0f} 行/秒")
# 6. 关闭 IDENTITY_INSERT
try: sql_cursor.execute(f"SET IDENTITY_INSERT {full_target_name} OFF")
except: pass
if identity_enabled:
try:
sql_cursor.execute(f"SET IDENTITY_INSERT {full_target_name} OFF")
logger.info(f" ✓ 已关闭 IDENTITY_INSERT")
except Exception as id_err:
logger.warning(f" ⚠️ 关闭 IDENTITY_INSERT 时警告: {id_err}")
sql_conn.commit()
print(f"\n ✅ 完成。")
# 显示最终统计
table_time = time.time() - table_start_time
final_rate = table_rows / table_time if table_time > 0 else 0
logger.info(f" ✅ 完成。共 {table_rows:,} 行 | 平均速率: {final_rate:,.0f} 行/秒 | 总用时: {format_duration(table_time)}")
success_tables += 1
total_rows += table_rows
except Exception as tbl_err:
print(f" ❌ 表级错误: {tbl_err}")
failed_tables += 1
logger.error(f" ❌ 表级错误: {tbl_err}", exc_info=True)
sql_conn.rollback()
# 确保清理 IDENTITY_INSERT 状态
try:
sql_cursor.execute(f"SET IDENTITY_INSERT {full_target_name} OFF")
except:
pass
acc_conn.close()
logger.info(f" ✓ Access 文件处理完成")
except Exception as file_err:
print(f" ❌ 文件级错误: {file_err}")
logger.error(f" ❌ 文件级错误: {file_err}", exc_info=True)
sql_conn.close()
print("\n=== 全量同步结束 ===")
# 总结统计
sync_time = time.time() - sync_start_time
logger.info("\n" + "="*60)
logger.info("=== 全量同步结束 ===")
logger.info(f"总表数: {total_tables} | 成功: {success_tables} | 失败: {failed_tables}")
logger.info(f"总行数: {total_rows:,} 行")
logger.info(f"总用时: {format_duration(sync_time)}")
if total_rows > 0 and sync_time > 0:
logger.info(f"整体平均速率: {total_rows/sync_time:,.0f} 行/秒")
logger.info("="*60)
if __name__ == "__main__":
run_full_sync()

188
run_incremental_sync.py
View File

@@ -6,182 +6,162 @@ import config
import db_utils
import logging
from logging.handlers import TimedRotatingFileHandler
from collections import defaultdict
# ================= 日志系统配置 (新增) =================
# ================= 日志系统配置 =================
def setup_logger():
"""
配置双向日志系统：控制台输出 + 按天轮转的文件日志
"""
# 1. 确保日志目录存在
log_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'log')
if not os.path.exists(log_dir):
os.makedirs(log_dir)
# 2. 创建 Logger
logger = logging.getLogger("SyncService")
logger.setLevel(logging.INFO)
logger.handlers = [] # 清除旧句柄，防止重复打印
logger.handlers = []
# 3. 文件处理器 (按天轮转)
# filename: 正在写入的日志名
# when='midnight': 每天午夜轮转
# interval=1: 间隔1天
# backupCount=30: 保留最近30个文件
log_file_path = os.path.join(log_dir, 'sync_service.log')
file_handler = TimedRotatingFileHandler(
log_file_path, when='midnight', interval=1, backupCount=30, encoding='utf-8'
)
file_handler.suffix = "%Y-%m-%d" # 轮转后的文件名后缀
# 文件日志格式：[时间] [级别] 消息
file_handler.suffix = "%Y-%m-%d"
file_fmt = logging.Formatter('%(asctime)s - [%(levelname)s] - %(message)s')
file_handler.setFormatter(file_fmt)
# 4. 控制台处理器 (屏幕输出)
console_handler = logging.StreamHandler(sys.stdout)
# 控制台日志格式：[时间] 消息 (保持简洁)
console_fmt = logging.Formatter('%(asctime)s - %(message)s', datefmt='%H:%M:%S')
console_handler.setFormatter(console_fmt)
# 5. 添加处理器
logger.addHandler(file_handler)
logger.addHandler(console_handler)
return logger
# 初始化全局 Logger
logger = setup_logger()
# ================= 辅助函数 =================
def clean_access_path(raw_addr):
"""清洗 TableAddress 字段"""
if not raw_addr: return ""
s = str(raw_addr).strip()
if s.upper().startswith(";DATABASE="): return s[10:]
if s.upper().startswith("LOCAL:"): return s[6:]
return s
def get_norm_path(path):
"""获取标准化路径"""
if not path: return ""
return os.path.normpath(path).lower()
# ================= 主逻辑 =================
def process_logs():
def process_sync_task():
"""
逻辑重构：
遍历 config.SYNC_MAPPING 中的每一个文件 -> 去日志表查询该文件下特定表的未同步记录。
"""
sql_conn = db_utils.get_sql_conn()
sql_cursor = sql_conn.cursor()
sql_cursor.fast_executemany = True
sql_cursor.fast_executemany = True # 高性能开关
# 标记是否有工作被处理（用于控制轮询休眠时间）
work_done = False
cols = config.LOG_TABLE_CONFIG
# --- 0. 预处理配置映射 ---
normalized_mapping = {}
for cfg_path, cfg_tables in config.SYNC_MAPPING.items():
norm_key = get_norm_path(cfg_path)
normalized_mapping[norm_key] = {
'original_path': cfg_path,
'tables': cfg_tables
}
try:
log_full_name = db_utils.fmt_table(cols['schema'], cols['table_name'])
# --- 1. 读取日志 ---
try:
# === 核心循环：以配置文件为驱动 ===
for clean_path, tables_map in config.SYNC_MAPPING.items():
# 1. 准备查询条件
# 获取该文件下所有需要同步的表名列表
target_tables = list(tables_map.keys())
if not target_tables:
continue
# 构造 TableAddress 的精确匹配条件
# VBA 逻辑：网络路径带 ";DATABASE=", 本地路径带 "LOCAL:"
# 我们直接构造这两个字符串，让 SQL Server 做精确匹配，效率极高
# 注意：将路径转为 Windows 标准反斜杠
win_path = os.path.normpath(clean_path)
addr_candidates = [
f";DATABASE={win_path}", # 情况1
f"LOCAL={win_path}", # 情况2 (注意 VBA 代码里可能是 LOCAL: 或 LOCAL=，请核对)
f"LOCAL:{win_path}", # 情况3
win_path # 情况4 (兼容没有前缀的情况)
]
# 2. 构造动态 SQL 查询
# WHERE Synced=0 AND Address IN (...) AND TableName IN (...)
placeholders_addr = ','.join(['?'] * len(addr_candidates))
placeholders_tbl = ','.join(['?'] * len(target_tables))
query_log = f"""
SELECT TOP 1000
{cols['col_log_id']},
{cols['col_table_name']},
{cols['col_record_id']},
{cols['col_address']}
{cols['col_record_id']}
FROM {log_full_name}
WHERE {cols['col_synced']} = 0
AND TableType = 'LINKED_ACCESS'
AND {cols['col_address']} IN ({placeholders_addr})
AND {cols['col_table_name']} IN ({placeholders_tbl})
ORDER BY {cols['col_log_id']} ASC
"""
sql_cursor.execute(query_log)
# 参数列表：先放地址，再放表名
params = addr_candidates + target_tables
sql_cursor.execute(query_log, params)
logs = sql_cursor.fetchall()
if not logs:
return False
continue # 这个文件没有需要同步的记录，检查下一个文件
logger.info(f"📥 收到 {len(logs)} 条链接表变更日志...")
# --- 2. 任务分组 ---
tasks = defaultdict(lambda: defaultdict(lambda: {'record_ids': set(), 'log_ids': []}))
work_done = True # 标记有工作
logger.info(f"📂 文件 {os.path.basename(clean_path)} 发现 {len(logs)} 条变更...")
# 3. 本地分组 (按表名)
# 结构: table_tasks[TableName] = { ids: {}, log_ids: [] }
table_tasks = {}
for row in logs:
log_id, acc_table, record_id, raw_address = row
log_id, acc_table, record_id = row
if acc_table not in table_tasks:
table_tasks[acc_table] = {'record_ids': set(), 'log_ids': []}
table_tasks[acc_table]['record_ids'].add(record_id)
table_tasks[acc_table]['log_ids'].append(log_id)
clean_path = clean_access_path(raw_address)
norm_lookup_key = get_norm_path(clean_path)
# 校验配置
if norm_lookup_key not in normalized_mapping:
# 记录一条警告日志，但不刷屏
logger.warning(f"忽略未配置的文件路径: {clean_path}")
continue
mapping_node = normalized_mapping[norm_lookup_key]
if acc_table not in mapping_node['tables']:
logger.warning(f"忽略未配置的表: {acc_table} (在文件 {os.path.basename(clean_path)} 中)")
continue
tasks[clean_path][acc_table]['record_ids'].add(record_id)
tasks[clean_path][acc_table]['log_ids'].append(log_id)
# --- 3. 执行同步循环 ---
for file_path, tables_data in tasks.items():
if not os.path.exists(file_path):
logger.error(f"无法访问文件: {file_path}")
# 4. 执行同步 (连接一次 Access，处理多张表)
if not os.path.exists(clean_path):
logger.error(f"无法访问文件: {clean_path}")
continue
try:
acc_conn = db_utils.get_access_conn(file_path)
acc_conn = db_utils.get_access_conn(clean_path)
acc_cursor = acc_conn.cursor()
except Exception as conn_err:
logger.error(f"连接 Access 失败 [{file_path}]: {conn_err}")
logger.error(f"连接 Access 失败: {conn_err}")
continue
norm_key = get_norm_path(file_path)
config_node = normalized_mapping[norm_key]
for acc_table, data in tables_data.items():
for acc_table, data in table_tasks.items():
record_ids = list(data['record_ids'])
log_ids = data['log_ids']
target_conf = config_node['tables'][acc_table]
# 读取目标配置
target_conf = tables_map[acc_table]
target_schema = target_conf['target_schema']
target_table = target_conf['target_table']
pk_col = target_conf['pk_col']
target_full_name = db_utils.fmt_table(target_schema, target_table)
try:
# --- A. Access 查新数据 ---
ids_placeholders = ','.join(['?'] * len(record_ids))
# A. Access 读取
acc_sql = f"SELECT * FROM [{acc_table}] WHERE [{pk_col}] IN ({ids_placeholders})"
acc_cursor.execute(acc_sql, record_ids)
new_rows = acc_cursor.fetchall()
acc_cols = [col[0] for col in acc_cursor.description]
# B. SQL Server 写入
# --- B. SQL Server 删旧插新 (事务) ---
# 1. 删除
del_sql = f"DELETE FROM {target_full_name} WHERE [{pk_col}] IN ({ids_placeholders})"
sql_cursor.execute(del_sql, record_ids)
# 2. 插入
if new_rows:
insert_sql = db_utils.generate_insert_sql(target_schema, target_table, acc_cols)
try: sql_cursor.execute(f"SET IDENTITY_INSERT {target_full_name} ON")
except: pass
sql_cursor.executemany(insert_sql, new_rows)
try: sql_cursor.execute(f"SET IDENTITY_INSERT {target_full_name} OFF")
except: pass
# C. 更新日志状态
# 3. 标记日志 Synced = 1
log_placeholders = ','.join(['?'] * len(log_ids))
update_log_sql = f"""
UPDATE {log_full_name}
@@ -191,15 +171,15 @@ def process_logs():
sql_cursor.execute(update_log_sql, log_ids)
sql_conn.commit()
logger.info(f"✅ 同步成功: {target_table} 更新 {len(record_ids)} 条 (来源: {os.path.basename(file_path)})")
logger.info(f" -> {target_table} 同步成功: {len(record_ids)} 条")
except Exception as tbl_err:
logger.error(f"处理表 {acc_table} 异常: {tbl_err}")
logger.error(f" -> 处理表 {acc_table} 异常: {tbl_err}")
sql_conn.rollback()
acc_conn.close()
acc_conn.close() # 关闭 Access 连接
return True
return work_done
except Exception as e:
logger.critical(f"全局严重异常: {e}")
@@ -209,14 +189,18 @@ def process_logs():
except: pass
if __name__ == "__main__":
logger.info("=== 增量同步服务已启动 (日志模式: log/sync_service.log) ===")
logger.info("=== 增量同步服务启动 (配置驱动模式) ===")
logger.info("正在按 config.SYNC_MAPPING 轮询...")
while True:
try:
has_work = process_logs()
time.sleep(0.5 if has_work else config.POLL_INTERVAL)
has_work = process_sync_task()
# 如果有工作，说明可能还有积压，休息短一点(0.1s)
# 如果没工作，休息标准间隔(5s)
time.sleep(0.1 if has_work else config.POLL_INTERVAL)
except KeyboardInterrupt:
logger.info("收到停止指令，服务正在关闭...")
logger.info("服务停止")
break
except Exception as e:
logger.critical(f"主循环崩溃: {e}")
time.sleep(5) # 防止死循环刷屏
time.sleep(5)

40
vbareplace.py
View File

@@ -29,7 +29,7 @@ def main():
if getattr(sys, 'frozen', False):
script_dir = os.path.dirname(sys.executable)
else:
script_dir = os.path.dirname(os.path.abspath(__file))
script_dir = os.path.dirname(os.path.abspath(__file__))
vba_txt_file = os.path.join(script_dir, "vba.txt")
@@ -46,8 +46,8 @@ def main():
return
try:
# 启动 Access
access = win32com.client.Dispatch("Access.Application")
# 启动 Access（使用 DispatchEx 强制创建新实例，避免与已打开的 Access 冲突）
access = win32com.client.DispatchEx("Access.Application")
access.Visible = False # 后台运行，不显示窗口
# 打开数据库
@@ -84,13 +84,45 @@ def main():
access.DoCmd.Close(0, form_name, 0) # 尝试关闭，避免卡住
print(f"处理窗体 {form_name} 时出错: {e}")
# 刷新所有链接表
refreshed_tables = 0
failed_tables = 0
try:
db = access.CurrentDb()
table_count = db.TableDefs.Count
for i in range(table_count):
table_def = db.TableDefs(i)
# 检查是否是链接表（Connect属性不为空）
if table_def.Connect:
try:
table_def.RefreshLink()
print(f"已刷新链接表: {table_def.Name}")
refreshed_tables += 1
except Exception as e:
print(f"刷新链接表 {table_def.Name} 失败: {e}")
failed_tables += 1
except Exception as e:
print(f"刷新链接表时出错: {e}")
access.CloseCurrentDatabase()
access.Quit()
messagebox.showinfo("成功", f"操作完成！\n\n已处理 {form_count} 个窗体，成功替换 {replaced} 个。\n\n文件已保存: {os.path.basename(access_file)}")
# 构建结果消息
result_msg = f"操作完成！\n\n"
result_msg += f"已处理 {form_count} 个窗体，成功替换 {replaced} 个。\n"
if refreshed_tables > 0 or failed_tables > 0:
result_msg += f"已刷新 {refreshed_tables} 个链接表"
if failed_tables > 0:
result_msg += f"，{failed_tables} 个失败"
result_msg += "。\n"
result_msg += f"\n文件已保存: {os.path.basename(access_file)}"
messagebox.showinfo("成功", result_msg)
except Exception as e:
messagebox.showerror("运行错误", f"操作失败:\n{e}\n\n请检查是否已启用 VBA 项目访问信任。")
if __name__ == "__main__":
main()
# pyinstaller --onefile --noconsole --name "VBA代码批量替换" vbareplace.py