zwf
527 lines
19 KiB
Python
527 lines
19 KiB
Python
import datetime
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import random
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from typing import Union
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import pandas as pd
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from sqlalchemy import select, delete
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from tornado_swagger.model import register_swagger_model
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from wtforms import StringField, IntegerField, TextAreaField
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from wtforms.validators import Length
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import models
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from models.common_model import CommonModel
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from models.db_models import TD3iGovcTaskAttachment
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from paste.core.logging import echo_log
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from paste.rbac.rbac_user import RbacUser
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from paste.util.pagination import Pagination
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from paste.web.form import ModelForm
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class GovcTaskAttachmentForm(ModelForm):
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"""
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工单附件表单验证类（完全映射 TD3iGovcTaskAttachment 字段）。
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用于验证和处理市12345工单附件的创建/修改表单数据。
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字段完全映射数据库表 t_d3i_govc_task_attachment 的字段结构。
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"""
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# 基础信息
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id = IntegerField('主键ID')
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task_id = IntegerField('关联工单主表ID', validators=[], # 外键非空由数据库约束，此处可补充自定义验证
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description='关联工单主表ID（t_d3i_govc_task.id）')
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detail_id = IntegerField('关联工单详情ID', validators=[],
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description='关联工单详情ID（t_d3i_govc_task_detail.id）')
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name = StringField('附件名称', validators=[Length(max=500, message='附件名称长度不能超过500字符')])
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attach_url = TextAreaField('附件地址', validators=[Length(max=65535, message='附件地址长度不能超过65535字符')])
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type = StringField('附件类型', validators=[Length(max=64, message='附件类型长度不能超过64字符')])
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created_at = StringField('创建时间', render_kw={'readonly': True})
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created_by = StringField('创建者', validators=[Length(max=64, message='创建者长度不能超过64字符')])
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updated_at = StringField('更新时间', render_kw={'readonly': True})
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updated_by = StringField('更新者', validators=[Length(max=64, message='更新者长度不能超过64字符')])
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def process(self, formdata=None, obj=None, **kwargs):
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"""
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处理表单数据，在数据绑定前进行预处理。
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主要功能：
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- 遍历所有表单字段
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- 对字符串类型的值去除两端空白字符
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- 调用父类的process方法继续处理
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"""
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if formdata:
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for name, values in formdata.items():
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if isinstance(values, list) and values:
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formdata[name] = [v.strip() if isinstance(v, str) else v for v in values]
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elif isinstance(values, str):
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formdata[name] = values.strip()
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super().process(formdata, obj, **kwargs)
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class GovcTaskAttachmentBase(TD3iGovcTaskAttachment, CommonModel):
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"""
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工单附件基础类（完全映射 TD3iGovcTaskAttachment 字段）。
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继承自数据库模型 TD3iGovcTaskAttachment 和通用模型 CommonModel。
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封装所有与工单附件相关的通用操作方法。
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"""
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FieldMapping = {
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'id': 'id',
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'task_id': 'task_id',
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'detail_id': 'detail_id',
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'name': 'name',
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'attach_url': 'attach_url',
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'type': 'type',
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'created_at': 'created_at',
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'created_by': 'created_by',
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'updated_at': 'updated_at',
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'updated_by': 'updated_by',
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}
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"""
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工单附件数据映射
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"""
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@classmethod
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async def is_exist(cls, task_id: int, detail_id: int, name: str):
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"""
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检查工单附件记录是否已存在（根据工单ID+详情ID+附件名称）。
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:param task_id: 关联工单主表ID
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:param detail_id: 关联工单详情ID
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:param name: 附件名称
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:return: 存在返回对象，不存在返回None
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"""
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_query = select(cls).where(
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cls.task_id == task_id,
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cls.detail_id == detail_id,
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cls.name == name
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)
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_attachment: cls = await cls.query_first(_query)
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return _attachment
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@classmethod
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async def search_base(cls, is_paging=True, **kwargs):
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"""
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按参数搜索工单附件数据的基础方法。
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支持字段：
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- 精确匹配：task_id, detail_id, type, created_by, updated_by
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- 模糊匹配：name, attach_url
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:param is_paging: 是否分页
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:param kwargs: 查询参数
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:key int page_number: 页码（缺省随机1~100）
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:key int page_size: 每页数量（缺省20）
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:key dict sort_clause: 排序配置，如 {'name': 'asc'}
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:key int task_id: 精确匹配关联工单主表ID
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:key int detail_id: 精确匹配关联工单详情ID
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:key str name: 模糊匹配附件名称
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:key str attach_url: 模糊匹配附件地址
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:key str type: 精确匹配附件类型
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:key str created_by: 精确匹配创建者
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:key str updated_by: 精确匹配更新者
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:return: (DataFrame, Pagination)
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"""
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page_number = kwargs.get('page_number', random.randint(1, 100))
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page_size = kwargs.get('page_size', 20)
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kwargs.update({'page_number': page_number, 'page_size': page_size})
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# 模糊查询字段
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_name_likes = {
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cls.name.key: '%{}%',
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cls.attach_url.key: '%{}%',
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}
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_query = select(cls).where(
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*cls.search_wheres(likes=_name_likes, **kwargs)
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).group_by(cls.id)
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_paging = None
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if is_paging:
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_row_count = await cls.query_count(_query)
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_paging = Pagination(_row_count).paging(page_number, page_size)
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_data_query = _query.limit(page_size).offset(_paging.offset_size)
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else:
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_data_query = _query
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_sort_clause = cls.sort_clauses(kwargs.get('sort_clause', {}))
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if _sort_clause:
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_data_query = _data_query.order_by(*_sort_clause)
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else:
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_data_query = _data_query.order_by(cls.task_id, cls.detail_id, cls.name)
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_attachment_df = await cls.query_as_df(_data_query)
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if not _attachment_df.empty:
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_attachment_df.replace(models.EmptyInDF + models.EmptyDatetimeInDF, '', inplace=True)
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_attachment_df[cls.id.key] = _attachment_df[cls.id.key].astype(str)
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_attachment_df[cls.task_id.key] = _attachment_df[cls.task_id.key].astype(str)
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_attachment_df[cls.detail_id.key] = _attachment_df[cls.detail_id.key].astype(str)
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return _attachment_df, _paging
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@classmethod
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async def search(cls, **kwargs):
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"""
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按参数搜索工单附件数据，返回分页格式数据。
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"""
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_attachment_df, _paging = await cls.search_base(** kwargs)
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return {
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'total': _paging.row_count,
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'rows': _attachment_df.to_dict('records'),
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'pagination': {
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'page_number': _paging.page_number,
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'page_count': _paging.page_count,
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'page_size': _paging.page_size,
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},
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}
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@classmethod
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async def exists_by_unique_key(cls, data_df: pd.DataFrame):
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"""
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查找 data_df 中在数据库中已存在和不存在的记录。
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根据 task_id + detail_id + name 组合判断唯一性。
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:param data_df: 输入的数据框架，必须包含 task_id、detail_id、name 列
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:return: (exists_df: pd.DataFrame, latest_df: pd.DataFrame)
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- exists_df: 在数据库中存在的记录（补充id字段）
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- latest_df: 在数据库中不存在的记录
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"""
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if data_df.empty:
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return pd.DataFrame(), pd.DataFrame()
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# 校验必要列
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required_cols = ['task_id', 'detail_id', 'name']
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missing_cols = [col for col in required_cols if col not in data_df.columns]
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if missing_cols:
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echo_log(f"错误：exists_by_unique_key 要求输入数据必须包含 {missing_cols} 列")
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return pd.DataFrame(), data_df.copy()
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# 去重并构建查询条件
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unique_keys = data_df[required_cols].drop_duplicates()
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if unique_keys.empty:
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return pd.DataFrame(), data_df.copy()
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# 构建批量查询条件
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_query_conditions = []
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for _, row in unique_keys.iterrows():
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_query_conditions.append(
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(cls.task_id == row['task_id']) &
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(cls.detail_id == row['detail_id']) &
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(cls.name == row['name'])
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)
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if not _query_conditions:
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return pd.DataFrame(), data_df.copy()
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# 查询数据库中已存在的记录
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_query = select(cls.id, cls.task_id, cls.detail_id, cls.name).where(
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* _query_conditions
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)
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exist_keys_df = await cls.query_as_df(_query)
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if exist_keys_df.empty:
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return pd.DataFrame(), data_df.copy()
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# 构建唯一键映射（task_id|detail_id|name -> id）
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exist_keys_df['unique_key'] = exist_keys_df.apply(
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lambda x: f"{x['task_id']}|{x['detail_id']}|{x['name']}", axis=1
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)
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data_df['unique_key'] = data_df.apply(
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lambda x: f"{x['task_id']}|{x['detail_id']}|{x['name']}", axis=1
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)
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key_to_id_map = dict(zip(exist_keys_df['unique_key'], exist_keys_df['id']))
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# 划分存在/不存在的记录
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mask_exists = data_df['unique_key'].isin(exist_keys_df['unique_key'])
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exists_df = data_df[mask_exists].copy()
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exists_df[cls.id.key] = exists_df['unique_key'].map(key_to_id_map)
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latest_df = data_df[~mask_exists].copy()
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# 清理临时列
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for df in [exists_df, latest_df]:
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if 'unique_key' in df.columns:
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df.drop('unique_key', axis=1, inplace=True)
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return exists_df, latest_df
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@register_swagger_model
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class GovcTaskAttachment(GovcTaskAttachmentBase):
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"""
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工单附件模型类（主业务类，完全继承 TD3iGovcTaskAttachment 字段）。
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---
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description: 市12345工单附件接口
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type: object
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properties:
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id:
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description: 主键ID
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type: integer
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example: 1001
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readOnly: true
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task_id:
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description: 关联工单主表ID
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type: integer
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example: 5001
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required: true
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detail_id:
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description: 关联工单详情ID
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type: integer
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example: 6001
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required: true
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name:
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description: 附件名称
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type: string
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example: "现场照片.jpg"
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maxLength: 500
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required: true
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attach_url:
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description: 附件地址
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type: string
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example: "/uploads/2024/05/现场照片.jpg"
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maxLength: 65535
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required: true
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type:
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description: 附件类型
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type: string
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example: "image/jpeg"
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maxLength: 64
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created_at:
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description: 创建时间，ISO格式的日期时间字符串
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type: string
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format: date-time
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example: "2024-01-15 10:30:00"
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readOnly: true
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created_by:
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description: 创建者用户名
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type: string
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example: "admin"
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maxLength: 64
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readOnly: true
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updated_at:
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description: 修改时间，ISO格式的日期时间字符串
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type: string
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format: date-time
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example: "2024-01-16 14:25:00"
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readOnly: true
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updated_by:
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description: 修改者用户名
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type: string
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example: "editor"
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maxLength: 64
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readOnly: true
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"""
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@classmethod
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async def create(cls, user: RbacUser = None, **kwargs):
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"""
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创建新的工单附件记录。
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业务流程：
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1. 使用 GovcTaskAttachmentForm 验证表单数据完整性
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2. 检查是否已存在相同 (task_id+detail_id+name) 的记录（避免重复提交）
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3. 创建新附件对象
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4. 设置创建者和更新者为当前用户
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5. 保存到数据库
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6. 返回创建的对象
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:param RbacUser user: 操作用户对象
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:param kwargs: 附件参数字典
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:return: 新建附件对象
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:rtype: GovcTaskAttachment
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:raises AssertionError: 当记录已存在时抛出
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:raises ValidationError: 当表单验证失败时抛出
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"""
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# 处理字符串字段去除空格
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for _k, _v in kwargs.items():
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if isinstance(_v, str):
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kwargs[_k] = _v.strip()
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_form = GovcTaskAttachmentForm(formdata=kwargs)
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_form.validate_form()
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# 检查是否已存在相同唯一键的记录
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_existing = await cls.is_exist(
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task_id=_form.task_id.data,
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detail_id=_form.detail_id.data,
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name=_form.name.data
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)
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assert _existing is None, "该工单下已存在同名附件，不能重复提交。"
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# 创建对象
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_attachment = cls().copy_from_dict(_form.data, skip_none=True).before_save()
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if user:
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_attachment.created_by = user.username
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_attachment.updated_by = user.username
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await _attachment.async_save()
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return _attachment
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@classmethod
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async def delete(cls, attachment_id: Union[str, int]):
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"""
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删除工单附件记录。
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业务流程：
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1. 根据ID查找记录
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2. 验证存在性
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3. 执行删除
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:param attachment_id: 要删除的附件记录ID
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:return: 删除的记录对象
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:rtype: GovcTaskAttachment
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:raises AssertionError: 当记录不存在时抛出
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"""
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_attachment: cls = await cls.async_find_by_id(attachment_id)
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assert _attachment, f"根据 ID {attachment_id} 未找到工单附件记录。"
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_del_query = delete(cls).where(cls.id == _attachment.id)
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_del_count = (await cls.raw_execute(_del_query)).rowcount
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echo_log(
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f'已删除工单附件记录（工单ID：{_attachment.task_id}，附件名称：{_attachment.name}，ID：{_attachment.id}）.')
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return _attachment
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@classmethod
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async def modify(cls, attachment_id: Union[str, int], user: RbacUser = None, **kwargs):
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"""
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修改已有工单附件记录。
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业务流程：
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1. 处理字符串字段去除首尾空格
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2. 使用 GovcTaskAttachmentForm 验证表单数据
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3. 查询原记录
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4. 验证存在性
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5. 更新字段并设置更新者
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6. 保存到数据库
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7. 返回更新后的对象
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:param attachment_id: 要修改的附件记录ID
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:param RbacUser user: 操作用户对象
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:param kwargs: 需要更新的字段
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:return: 修改后的附件对象
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:rtype: GovcTaskAttachment
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:raises AssertionError: 当记录不存在时抛出
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:raises ValidationError: 当表单验证失败时抛出
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"""
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# 处理字符串字段去除空格
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for _k, _v in kwargs.items():
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if isinstance(_v, str):
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kwargs[_k] = _v.strip()
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# 表单验证
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_form = GovcTaskAttachmentForm(formdata=kwargs)
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_form.validate_form()
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# 查询原记录
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_attachment: cls = await cls.async_find_by_id(attachment_id)
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assert _attachment, f'查无此工单附件信息。'
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# 更新字段
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_attachment.copy_from_dict(_form.data, skip_none=True).before_save()
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_attachment.updated_by = user.username if user else _attachment.updated_by
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await _attachment.async_save()
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return _attachment
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@classmethod
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async def create_batch(cls, data_df: pd.DataFrame, user: RbacUser = None):
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"""
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批量创建工单附件记录（传入数据应为全新记录）。
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:param data_df: 包含附件数据的 DataFrame
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:param user: 操作用户对象，用于设置 created_by / updated_by
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:return: 成功创建的数量
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:rtype: int
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"""
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if data_df.empty:
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return 0
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# 补充创建者/更新者信息
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if user:
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data_df['created_by'] = user.username
|
||
data_df['updated_by'] = user.username
|
||
|
||
# 数据预处理（去空格）
|
||
str_cols = ['name', 'attach_url', 'type', 'created_by', 'updated_by']
|
||
for col in str_cols:
|
||
if col in data_df.columns:
|
||
data_df[col] = data_df[col].apply(lambda x: x.strip() if isinstance(x, str) else x)
|
||
|
||
records = data_df.to_dict('records')
|
||
attachments = [cls().copy_from_dict(record, skip_none=True).before_save() for record in records]
|
||
|
||
session = cls.get_aio_session()
|
||
try:
|
||
session.add_all(attachments)
|
||
await session.commit()
|
||
except Exception as e:
|
||
await session.rollback()
|
||
raise e
|
||
finally:
|
||
await session.close()
|
||
echo_log(f"批量创建成功：创建 {len(attachments)} 条工单附件记录。")
|
||
return len(attachments)
|
||
|
||
@classmethod
|
||
async def modify_batch(cls, data_df: pd.DataFrame, user: RbacUser = None):
|
||
"""
|
||
批量修改已有工单附件记录。
|
||
|
||
:param data_df: 包含附件数据的 DataFrame（必须包含 id 列）
|
||
:param user: 操作用户对象，用于设置 updated_by
|
||
:return: 成功更新的数量
|
||
:rtype: int
|
||
"""
|
||
if data_df.empty:
|
||
return 0
|
||
|
||
# 必须包含 id 列
|
||
if 'id' not in data_df.columns:
|
||
echo_log(f"错误：modify_batch 要求输入数据必须包含 '{cls.id.key}' 列（主键）")
|
||
return 0
|
||
|
||
# 数据预处理（去空格）
|
||
str_cols = ['name', 'attach_url', 'type', 'updated_by']
|
||
for col in str_cols:
|
||
if col in data_df.columns:
|
||
data_df[col] = data_df[col].apply(lambda x: x.strip() if isinstance(x, str) else x)
|
||
|
||
# 手动添加更新时间戳
|
||
data_df['updated_at'] = datetime.datetime.now()
|
||
# 添加更新者信息
|
||
if user:
|
||
data_df['updated_by'] = user.username
|
||
|
||
# 转换为字典列表
|
||
update_data = data_df.to_dict('records')
|
||
|
||
# 使用 bulk_update_mappings 批量更新
|
||
session = cls.get_aio_session()
|
||
try:
|
||
await session.run_sync(
|
||
lambda sync_session: sync_session.bulk_update_mappings(cls, update_data)
|
||
)
|
||
await session.commit()
|
||
updated_count = len(update_data)
|
||
except Exception as e:
|
||
await session.rollback()
|
||
raise e
|
||
finally:
|
||
await session.close()
|
||
|
||
echo_log(f"批量修改成功：更新 {updated_count} 条工单附件记录。")
|
||
return updated_count
|
||
|
||
@classmethod
|
||
async def save_batch(cls, data_df: pd.DataFrame, user: RbacUser = None):
|
||
"""
|
||
批量保存工单附件数据，自动处理新建和更新。
|
||
|
||
:param data_df: 要保存的数据框架（需包含 task_id、detail_id、name 列）
|
||
:param user: 操作用户对象
|
||
:return: (created_count, updated_count) 新建和更新的数量
|
||
"""
|
||
# 筛选数据状态（按唯一键判断存在性）
|
||
_exists_df, _latest_df = await cls.exists_by_unique_key(data_df)
|
||
# 批量创建/更新
|
||
_created_count = await cls.create_batch(_latest_df, user)
|
||
_updated_count = await cls.modify_batch(_exists_df, user)
|
||
return _created_count, _updated_count |