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282 lines
12 KiB
282 lines
12 KiB
from module_admin.entity.vo.user_vo import *
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from module_admin.entity.vo.vecset_vo import *
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from module_admin.entity.vo.dasset_vo import *
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from module_admin.dao.vecset_dao import *
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from module_admin.dao.dasset_dao import *
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from utils.pwd_util import *
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from utils.common_util import *
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class VecsetService:
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"""
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智能语句配置模块服务层
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"""
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@classmethod
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def get_vecset_list_services(cls, result_db: Session, query_object: VecsetQueryModel, data_scope_sql: str):
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"""
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获取智能语句配置信息service
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:param result_db: orm对象
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:param query_object: 查询参数对象
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:param data_scope_sql: 数据权限对应的查询sql语句
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:return: 字段列表信息对象
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"""
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vecset_list_result = VecsetDao.get_vecset_list(result_db, query_object, data_scope_sql)
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#test_asset = SysDasset.get_dasset_detail_by_dname(result_db,dasset_name='资讯数据资产')
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#print(test_asset,99999999)
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return vecset_list_result
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@classmethod
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def add_vecset_services(cls, result_db: Session, page_object: AddVecsetModel):
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"""
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新增智能语句配置信息service
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:param result_db: orm对象
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:param page_object: 新增智能语句配置对象
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:return: 新增字段校验结果
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"""
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add_vecset = VecsetModel(**page_object.dict())
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vecset = VecsetDao.get_vecset_by_info(result_db, VecsetModel(**dict(stab_name=page_object.stab_name)))
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if vecset:
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result = dict(is_success=False, message='字段名已存在')
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else:
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try:
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add_result = VecsetDao.add_vecset_dao(result_db, add_vecset)
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onum = add_result.onum
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result_db.commit()
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result = dict(is_success=True, message='新增成功')
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except Exception as e:
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result_db.rollback()
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result = dict(is_success=False, message=str(e))
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return CrudVecsetResponse(**result)
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@classmethod
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def edit_vecset_services(cls, result_db: Session, page_object: AddVecsetModel):
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"""
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编辑智能语句配置信息service
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:param result_db: orm对象
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:param page_object: 编辑智能语句配置对象
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:return: 编辑智能语句配置校验结果
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"""
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edit_vecset = page_object.dict(exclude_unset=True)
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if page_object.type == 'status' or page_object.type == 'avatar':
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del edit_vecset['type']
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vecset_info = cls.detail_vecset_services(result_db, edit_vecset.get('onum'))
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if vecset_info:
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if page_object.type != 'status' and page_object.type != 'avatar' and vecset_info.vecset.stab_name != page_object.stab_name:
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vecset = VecsetDao.get_vecset_by_info(result_db, VecsetModel(**dict(stab_name=page_object.stab_name)))
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if vecset:
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result = dict(is_success=False, message='字段名已存在')
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return CrudVecsetResponse(**result)
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try:
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VecsetDao.edit_vecset_dao(result_db, edit_vecset)
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if page_object.type != 'status' and page_object.type != 'avatar':
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onum_dict = dict(onum=page_object.onum)
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result_db.commit()
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result = dict(is_success=True, message='更新成功')
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except Exception as e:
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result_db.rollback()
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result = dict(is_success=False, message=str(e))
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else:
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result = dict(is_success=False, message='字段不存在')
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return CrudVecsetResponse(**result)
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@classmethod
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def delete_vecset_services(cls, result_db: Session, page_object: DeleteVecsetModel):
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"""
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删除智能语句配置信息service
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:param result_db: orm对象
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:param page_object: 删除智能语句配置对象
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:return: 删除智能语句配置校验结果
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"""
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if page_object.onums.split(','):
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onum_list = page_object.onums.split(',')
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try:
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for onum in onum_list:
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onum_dict = dict(onum=onum, update_by=page_object.update_by, update_time=page_object.update_time) #
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VecsetDao.delete_vecset_dao(result_db, VecsetModel(**onum_dict))
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result_db.commit()
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result = dict(is_success=True, message='删除成功')
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except Exception as e:
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result_db.rollback()
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result = dict(is_success=False, message=str(e))
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else:
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result = dict(is_success=False, message='传入智能语句配置id为空')
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return CrudVecsetResponse(**result)
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@classmethod
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def detail_vecset_services(cls, result_db: Session, onum: int):
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"""
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获取智能语句配置详细信息service
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:param result_db: orm对象
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:param onum: 智能语句配置id
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:return: 智能语句配置id对应的信息
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"""
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vecset = VecsetDao.get_vecset_detail_by_id(result_db, onum=onum)
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return VecsetDetailModel(
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vecset=vecset.vecset_basic_info,
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dasset=vecset.vecset_dasset_info
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)
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@staticmethod
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def export_vecset_list_services(vecset_list: List):
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"""
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导出配置表信息service
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:param vecset_list: 代码信息列表
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:return: 配置表信息对应excel的二进制数据
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"""
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# 创建一个映射代码，将英文键映射到中文键
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mapping_dict = {
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"dasset_id": "数据域名",
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"onum": "序号",
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"stab_name": "表名称",
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"squery": "查询语句",
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"sanal_plan": "分析方法",
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"sintnt_term": "意图词",
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"ssql": "参考sql",
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"sim_thrsh": "相似阈值",
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"status": "状态",
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# "create_by": "创建者",
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# "create_time": "创建时间",
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# "update_by": "更新者",
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# "update_time": "更新时间",
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}
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#data = [VecsetModel(**vars(row)).dict() for row in vecset_list]
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data = [VecsetModel(**row).dict() for row in vecset_list]
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for item in data:
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if item.get('status') == '0':
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item['status'] = '正常'
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else:
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item['status'] = '停用'
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if item.get('dasset_id') == 101:
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item['dasset_id'] = '资讯域'
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elif item.get('dasset_id') == 102:
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item['dasset_id'] = '财务域'
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elif item.get('dasset_id') == 145:
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item['dasset_id'] = '账户域'
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else:
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item['dasset_id'] == '其他域'
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new_data = [{mapping_dict.get(key): value for key, value in item.items() if mapping_dict.get(key)} for item in data]
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binary_data = export_list2excel(new_data)
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return binary_data
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@classmethod
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def batch_import_vecset_services(cls, result_db: Session, vecset_import: ImportVecsetModel, current_user: CurrentUserInfoServiceResponse):
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"""
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批量导入智能语句配置表service
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:param vecset_import: 智能语句配置表导入参数对象
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:param result_db: orm对象
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:param current_vecset: 当前智能语句配置表对象
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:return: 批量导入智能语句配置表结果
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"""
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header_dict = {
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"数据域名": "dasset_id",
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#"序号": "onum",
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"表名称": "stab_name",
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"查询语句": "squery",
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"分析方法": "sanal_plan",
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"意图词": "sintnt_term",
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"参考sql": "ssql",
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"相似阈值": "sim_thrsh",
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"状态": "status"
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}
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filepath = get_filepath_from_url(vecset_import.url)
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df = pd.read_excel(filepath)
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df.rename(columns=header_dict, inplace=True)
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add_error_result = []
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count = 0
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# VecsetDao.get_vecset_by_info(result_db, VecsetModel(**dict(stab_name=page_object.stab_name)))
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try:
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for index, row in df.iterrows():
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count = count + 1
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if row['dasset_id'] == '资讯域':
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row['dasset_id'] = '101'
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if row['dasset_id'] == '财务域':
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row['dasset_id'] = '102'
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if row['dasset_id'] == '其他域':
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row['dasset_id'] = '121'
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if row['status'] == '正常':
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row['status'] = '0'
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if row['status'] == '停用':
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row['status'] = '1'
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add_vecset = VecsetModel(
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**dict(
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dasset_id=row['dasset_id'],
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#onum=row['onum'],
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stab_name = str(row['stab_name']).replace('nan', ''),
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squery = str(row['squery']).replace('nan', ''),
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sanal_plan = str(row['sanal_plan']).replace('nan', ''),
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sintnt_term = str(row['sintnt_term']).replace('nan', ''),
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ssql = str(row['ssql']).replace('nan', ''),
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sim_thrsh = str(row['sim_thrsh']).replace('nan', ''),
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status=row['status'],
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create_by=current_user.user.user_name,
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update_by=current_user.user.user_name,
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)
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)
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vecset_info = VecsetDao.get_vecset_by_info_imp(result_db, VecsetModel(**dict(squery=row['squery'])))
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if vecset_info:
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if vecset_import.is_update:
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edit_vecset = VecsetModel(
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**dict(
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dasset_id=row['dasset_id'],
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#onum=row['onum'],
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stab_name = str(row['stab_name']).replace('nan', ''),
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squery = str(row['squery']).replace('nan', ''),
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sanal_plan = str(row['sanal_plan']).replace('nan', ''),
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sintnt_term = str(row['sintnt_term']).replace('nan', ''),
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ssql = str(row['ssql']).replace('nan', ''),
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sim_thrsh = str(row['sim_thrsh']).replace('nan', ''),
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status=row['status'],
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update_by=current_user.user.user_name
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)
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).dict(exclude_unset=True)
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VecsetDao.edit_vecset_dao(result_db, edit_vecset)
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else:
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add_error_result.append(f"{count}.用户账号{row['user_name']}已存在")
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else:
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VecsetDao.add_vecset_dao(result_db, add_vecset)
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result_db.commit()
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result = dict(is_success=True, message='\n'.join(add_error_result))
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except Exception as e:
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result_db.rollback()
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result = dict(is_success=False, message=str(e))
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return CrudVecsetResponse(**result)
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@staticmethod
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def get_vecset_import_template_services():
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"""
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获取智能语句配置表导入模板service
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:return: 智能语句配置表导入模板excel的二进制数据
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"""
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#header_list = ["数据域名", "序号", "查询语句", "分析方法", "意图词", "表名称", "参考sql", "相似阈值", "状态"]
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header_list = ["数据域名","表名称", "查询语句", "分析方法", "意图词", "参考sql", "相似阈值", "状态"]
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selector_header_list = ["数据域名","状态"]
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option_list = [{"数据域名": ["资讯域", "财务域", "账户域", "其他域"]},{"状态": ["正常", "停用"]}]
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binary_data = get_excel_template(header_list=header_list, selector_header_list=selector_header_list, option_list=option_list)
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return binary_data
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