185 lines
6.9 KiB
Python
185 lines
6.9 KiB
Python
from .base_sync import BaseSync
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from loguru import logger
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from typing import List, Dict
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from sqlalchemy import text
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from models.orm_models import StrategyKX
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class AccountSyncBatch(BaseSync):
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"""账户信息批量同步器"""
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async def sync_batch(self, accounts: Dict[str, Dict]):
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"""批量同步所有账号的账户信息"""
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try:
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logger.info(f"开始批量同步账户信息，共 {len(accounts)} 个账号")
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# 测试
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# res = await self.redis_client._get_account_info_from_redis(10140, 5548, 'mt5')
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# print(res)
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# return
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# 收集所有账号的数据
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all_account_data = await self.redis_client._collect_all_account_data(accounts)
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if not all_account_data:
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logger.info("无账户信息数据需要同步")
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return
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# 批量同步到数据库
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success = await self._sync_account_info_batch_to_db(all_account_data)
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if success:
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logger.info(f"账户信息批量同步完成: 处理 {len(all_account_data)} 条记录")
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else:
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logger.error("账户信息批量同步失败")
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except Exception as e:
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logger.error(f"账户信息批量同步失败: {e}")
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async def _sync_account_info_batch_to_db(self, account_data_list: List[Dict]) -> bool:
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"""批量同步账户信息到数据库（最高效版本）"""
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session = self.db_manager.get_session()
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try:
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if not account_data_list:
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return True
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with session.begin():
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# 方法1：使用原生SQL批量插入/更新（性能最好）
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success = self._batch_upsert_account_info(session, account_data_list)
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if not success:
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# 方法2：回退到ORM批量操作
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success = self._batch_orm_upsert_account_info(session, account_data_list)
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return success
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except Exception as e:
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logger.error(f"批量同步账户信息到数据库失败: {e}")
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return False
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finally:
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session.close()
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def _batch_upsert_account_info(self, session, account_data_list: List[Dict]) -> bool:
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"""使用原生SQL批量插入/更新账户信息"""
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try:
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# 准备批量数据
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values_list = []
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for data in account_data_list:
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values = (
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f"({data['st_id']}, {data['k_id']}, 'USDT', "
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f"{data['balance']}, {data['withdrawal']}, {data['deposit']}, "
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f"{data['other']}, {data['profit']}, {data['time']})"
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)
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values_list.append(values)
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if not values_list:
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return True
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values_str = ", ".join(values_list)
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# 使用INSERT ... ON DUPLICATE KEY UPDATE
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sql = f"""
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INSERT INTO deh_strategy_kx_new
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(st_id, k_id, asset, balance, withdrawal, deposit, other, profit, time)
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VALUES {values_str}
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ON DUPLICATE KEY UPDATE
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balance = VALUES(balance),
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withdrawal = VALUES(withdrawal),
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deposit = VALUES(deposit),
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other = VALUES(other),
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profit = VALUES(profit),
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up_time = NOW()
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"""
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session.execute(text(sql))
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logger.info(f"原生SQL批量更新账户信息: {len(account_data_list)} 条记录")
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return True
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except Exception as e:
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logger.error(f"原生SQL批量更新账户信息失败: {e}")
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return False
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def _batch_orm_upsert_account_info(self, session, account_data_list: List[Dict]) -> bool:
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"""使用ORM批量插入/更新账户信息"""
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try:
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# 分组数据以提高效率
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account_data_by_key = {}
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for data in account_data_list:
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key = (data['k_id'], data['st_id'], data['time'])
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account_data_by_key[key] = data
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# 批量查询现有记录
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existing_records = self._batch_query_existing_records(session, list(account_data_by_key.keys()))
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# 批量更新或插入
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to_update = []
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to_insert = []
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for key, data in account_data_by_key.items():
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if key in existing_records:
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# 更新
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record = existing_records[key]
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record.balance = data['balance']
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record.withdrawal = data['withdrawal']
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record.deposit = data['deposit']
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record.other = data['other']
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record.profit = data['profit']
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else:
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# 插入
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to_insert.append(StrategyKX(**data))
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# 批量插入新记录
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if to_insert:
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session.add_all(to_insert)
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logger.info(f"ORM批量更新账户信息: 更新 {len(existing_records)} 条，插入 {len(to_insert)} 条")
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return True
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except Exception as e:
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logger.error(f"ORM批量更新账户信息失败: {e}")
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return False
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def _batch_query_existing_records(self, session, keys: List[tuple]) -> Dict[tuple, StrategyKX]:
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"""批量查询现有记录"""
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existing_records = {}
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try:
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if not keys:
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return existing_records
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# 构建查询条件
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conditions = []
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for k_id, st_id, time_val in keys:
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conditions.append(f"(k_id = {k_id} AND st_id = {st_id} AND time = {time_val})")
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if conditions:
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conditions_str = " OR ".join(conditions)
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sql = f"""
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SELECT * FROM deh_strategy_kx_new
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WHERE {conditions_str}
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"""
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results = session.execute(text(sql)).fetchall()
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for row in results:
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key = (row.k_id, row.st_id, row.time)
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existing_records[key] = StrategyKX(
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id=row.id,
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st_id=row.st_id,
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k_id=row.k_id,
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asset=row.asset,
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balance=row.balance,
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withdrawal=row.withdrawal,
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deposit=row.deposit,
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other=row.other,
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profit=row.profit,
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time=row.time
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)
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except Exception as e:
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logger.error(f"批量查询现有记录失败: {e}")
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return existing_records
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