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导出优化，上传端代码

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liyxie
2025-11-08 10:36:24 +08:00
parent 5ee83477e3
commit 7633e22d99
7 changed files with 865 additions and 55 deletions
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117
app/services/export_excel.py
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@@ -10,6 +10,7 @@ from ..services.checkpoint import CheckpointService
from ..services.settlement_data import SettlementDataService
from ..services.level_data import LevelDataService
from ..services.account import AccountService
from ..core.exceptions import DataNotFoundException, AccountNotFoundException
import pandas as pd
import logging
from datetime import datetime
@@ -37,7 +38,7 @@ class ExportExcelService:
settlement_data: SettlementData,
section_data: SectionData,
checkpoint_data: Checkpoint,
level_data: LevelData) -> Dict[str, Any]:
level_data: Optional[LevelData]) -> Dict[str, Any]:
"""
合并沉降数据与关联数据，去除重复和id字段
"""
@@ -75,20 +76,21 @@ class ExportExcelService:
result[f"观测点_{key}"] = value
# 水准数据字段映射（添加前缀）
level_comments = self.get_field_comments(LevelData)
level_dict = level_data.to_dict()
for field_name, value in level_dict.items():
# 跳过id和NYID字段（NYID可能重复）
if field_name in ['id', 'NYID']:
continue
key = level_comments.get(field_name, field_name)
result[f"水准_{key}"] = value
if level_data is not None:
level_comments = self.get_field_comments(LevelData)
level_dict = level_data.to_dict()
for field_name, value in level_dict.items():
# 跳过id和NYID字段（NYID可能重复）
if field_name in ['id', 'NYID']:
continue
key = level_comments.get(field_name, field_name)
result[f"水准_{key}"] = value
return result
def export_settlement_data_to_file(self, db: Session, project_name: str, file_path: str):
"""
根据项目名称导出沉降数据Excel文件到指定路径
根据项目名称导出沉降数据Excel文件到指定路径（批量查询优化版本）
"""
logger.info(f"开始导出项目 '{project_name}' 的沉降数据到文件: {file_path}")
@@ -96,63 +98,92 @@ class ExportExcelService:
account_responses = self.account_service.search_accounts(db, project_name=project_name)
if not account_responses:
logger.warning(f"未找到项目名称为 '{project_name}' 的账号")
raise ValueError(f"未找到项目名称为 '{project_name}' 的账号")
raise AccountNotFoundException(f"未找到项目名称为 '{project_name}' 的账号")
account_response = account_responses[0]
account_id = str(account_response.id)
account_id = str(account_response.account_id)
logger.info(f"找到账号 ID: {account_id}")
# 2. 通过 account_id 查询断面数据
sections = self.section_service.search_section_data(db, account_id=account_id, limit=10000)
if not sections:
logger.warning(f"账号 {account_id} 下未找到断面数据")
raise ValueError(f"账号 {account_id} 下未找到断面数据")
raise DataNotFoundException(f"账号 {account_id} 下未找到断面数据")
logger.info(f"找到 {len(sections)} 个断面")
all_settlement_records = []
# 3. 收集所有观测点数据，建立断面->观测点映射
section_dict = {section.section_id: section for section in sections}
section_checkpoint_map = {} # section_id -> [checkpoints]
all_checkpoints = []
# 3-6. 遍历断面数据，查询关联数据
for section in sections:
section_id = section.section_id
logger.debug(f"处理断面: {section_id}")
checkpoints = self.checkpoint_service.get_by_section_id(db, section.section_id)
if checkpoints:
section_checkpoint_map[section.section_id] = checkpoints
all_checkpoints.extend(checkpoints)
# 3. 通过断面数据的section_id查询观测点数据
checkpoints = self.checkpoint_service.get_by_section_id(db, section_id)
if not checkpoints:
logger.debug(f"断面 {section_id} 下未找到观测点数据")
continue
if not all_checkpoints:
logger.warning("未找到任何观测点数据")
raise DataNotFoundException("未找到任何观测点数据")
logger.info(f"找到 {len(all_checkpoints)} 个观测点")
# 4. 批量查询沉降数据（关键优化点）
point_ids = [cp.point_id for cp in all_checkpoints]
logger.info(f"开始批量查询 {len(point_ids)} 个观测点的沉降数据")
all_settlements = self.settlement_service.get_by_point_ids(db, point_ids)
if not all_settlements:
logger.warning("未找到任何沉降数据")
logger.info(f"观测点id集合{point_ids}")
raise DataNotFoundException("未找到任何沉降数据")
logger.info(f"批量查询到 {len(all_settlements)} 条沉降数据")
# 5. 建立观测点->沉降数据映射
checkpoint_dict = {cp.point_id: cp for cp in all_checkpoints}
point_settlement_map = {} # point_id -> [settlements]
nyid_set = set()
for settlement in all_settlements:
if settlement.point_id not in point_settlement_map:
point_settlement_map[settlement.point_id] = []
point_settlement_map[settlement.point_id].append(settlement)
if settlement.NYID:
nyid_set.add(settlement.NYID)
# 6. 批量查询水准数据（关键优化点）
nyid_list = list(nyid_set)
logger.info(f"开始批量查询 {len(nyid_list)} 个期数的水准数据")
all_level_data = self.level_service.get_by_nyids(db, nyid_list)
logger.info(f"批量查询到 {len(all_level_data)} 条水准数据")
# 建立NYID->水准数据映射
nyid_level_map = {}
for level_data in all_level_data:
if level_data.NYID not in nyid_level_map:
nyid_level_map[level_data.NYID] = level_data
# 7. 合并数据
all_settlement_records = []
for section in sections:
checkpoints = section_checkpoint_map.get(section.section_id, [])
for checkpoint in checkpoints:
point_id = checkpoint.point_id
# 4. 通过观测点数据的point_id查询沉降数据集
settlements = self.settlement_service.get_by_point_id(db, point_id)
if not settlements:
logger.debug(f"观测点 {point_id} 下未找到沉降数据")
continue
settlements = point_settlement_map.get(checkpoint.point_id, [])
for settlement in settlements:
nyid = settlement.NYID
# 从映射中获取水准数据
level_data = nyid_level_map.get(settlement.NYID)
# 5. 通过沉降数据的NYID查询水准数据
level_data_list = self.level_service.get_by_nyid(db, nyid)
if not level_data_list:
logger.warning(f"期数 {nyid} 下未找到水准数据")
# 即使没有水准数据，也继续处理
level_data = None
else:
level_data = level_data_list[0]
# 6. 合并数据
# 合并数据
merged_record = self.merge_settlement_with_related_data(
db, settlement, section, checkpoint, level_data
)
all_settlement_records.append(merged_record)
if not all_settlement_records:
logger.warning("未找到任何沉降数据")
raise ValueError("未找到任何沉降数据")
logger.warning("未能合并任何数据记录")
raise DataNotFoundException("未能合并任何数据记录")
logger.info(f"共找到 {len(all_settlement_records)} 条沉降数据记录")