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import datetime
import random
from typing import Union
import pandas as pd
from sqlalchemy import select, delete
from tornado_swagger.model import register_swagger_model
from wtforms import StringField, TextAreaField, IntegerField
from wtforms.validators import Length
import models
from models.common_model import CommonModel
from models.db_models import TD3iDcmDispose
from paste.core.logging import echo_log
from paste.rbac.rbac_user import RbacUser
from paste.util.pagination import Pagination
from paste.web.form import ModelForm
class DcmDisposeForm(ModelForm):
"""
批转任务表单验证类(完全映射 TD3iDcmDispose 字段)。
用于验证和处理数字城管-批转任务的创建/修改表单数据。
字段完全映射数据库表 t_d3i_dcm_dispose 的字段结构。
"""
# 基础信息
id = IntegerField('记录ID')
rec_id = StringField('记录ID', validators=[Length(max=64, message='记录ID长度不能超过64字符')])
task_number = StringField('任务号', validators=[Length(max=64, message='任务号长度不能超过64字符')])
act_id = StringField('工单ID', validators=[Length(max=64, message='工单ID长度不能超过64字符')])
task_list_id = StringField('任务列表ID', validators=[Length(max=64, message='任务列表ID长度不能超过64字符')])
trans_info = StringField('批转对象', validators=[Length(max=64, message='批转对象长度不能超过64字符')])
opinion = TextAreaField('批转意见', validators=[Length(max=65535, message='批转意见长度不能超过65535字符')])
add_num = StringField('批转意见', validators=[Length(max=32, message='批转意见长度不能超过32字符')])
attachments = TextAreaField('附件', validators=[Length(max=65535, message='附件长度不能超过65535字符')])
send_message = StringField('发送短信', validators=[Length(max=32, message='发送短信标识长度不能超过32字符')])
undertake_user_name = StringField('承办人员', validators=[Length(max=64, message='承办人员长度不能超过64字符')])
undertake_phone = StringField('联系电话', validators=[Length(max=64, message='联系电话长度不能超过64字符')])
status = IntegerField('提交状态')
def process(self, formdata=None, obj=None, **kwargs):
"""
处理表单数据,在数据绑定前进行预处理。
主要功能:
- 遍历所有表单字段
- 对字符串类型的值去除两端空白字符
- 调用父类的process方法继续处理
"""
if formdata:
for name, values in formdata.items():
if isinstance(values, list) and values:
formdata[name] = [v.strip() if isinstance(v, str) else v for v in values]
elif isinstance(values, str):
formdata[name] = values.strip()
super().process(formdata, obj, **kwargs)
class DcmDisposeBase(TD3iDcmDispose, CommonModel):
"""
批转任务基础类(完全映射 TD3iDcmDispose 字段)。
继承自数据库模型 TD3iDcmDispose 和通用模型 CommonModel。
封装所有与批转任务相关的通用操作方法。
"""
FieldMapping = {
'id': 'id',
'rec_id': 'rec_id',
'task_number': 'task_number',
'act_id': 'act_id',
'task_list_id': 'task_list_id',
'trans_info': 'trans_info',
'opinion': 'opinion',
'add_num': 'add_num',
'attachments': 'attachments',
'send_message': 'send_message',
'undertake_user_name': 'undertake_user_name',
'undertake_phone': 'undertake_phone',
'status': 'status',
'created_at': 'created_at',
'created_by': 'created_by',
'updated_at': 'updated_at',
'updated_by': 'updated_by',
}
"""
批转任务数据映射
"""
@classmethod
async def exist_other(cls, id: Union[str, int], rec_id: str, task_number: str):
"""
检查是否存在除当前记录外的其他相同任务号或记录ID的批转记录。
:param id: 当前记录ID
:param rec_id: 记录ID
:param task_number: 任务号
:return: 存在返回记录对象,不存在返回None
"""
_query = select(cls).where(
cls.id != id,
(cls.rec_id == rec_id) | (cls.task_number == task_number)
)
_dispose: cls = await cls.query_first(_query)
return _dispose
@classmethod
async def find_by_ids(cls, ids: list[Union[str, int]]):
"""
根据ID列表批量查找批转任务数据。
"""
_query = select(cls).where(cls.id.in_(ids))
_dispose_list: list[cls] = (await cls.orm_execute_scalars(_query)).all()
return _dispose_list
@classmethod
async def is_exist(cls, rec_id: str, task_number: str):
"""
检查批转记录是否已经存在(根据记录ID或任务号)。
"""
_query = select(cls).where(
(cls.rec_id == rec_id) | (cls.task_number == task_number)
)
_dispose: cls = await cls.query_first(_query)
return _dispose
@classmethod
async def search_base(cls, is_paging=True, **kwargs):
"""
按参数搜索批转任务数据的基础方法。
支持字段:
- task_number, rec_id, act_id, trans_info, status
- 支持模糊匹配:trans_info, opinion
- 支持精确匹配:status, send_message
:param is_paging: 是否分页
:param kwargs: 查询参数
:key int page_number: 页码(缺省随机1~100
:key int page_size: 每页数量(缺省20
:key dict sort_clause: 排序配置,如 {'task_number': 'asc'}
:key str task_number: 精确匹配任务号
:key str rec_id: 精确匹配记录ID
:key str act_id: 精确匹配工单ID
:key str trans_info: 模糊匹配批转对象
:key str opinion: 模糊匹配批转意见
:key int status: 精确匹配提交状态
:key str send_message: 精确匹配发送短信标识
:return: (DataFrame, Pagination)
"""
page_number = kwargs.get('page_number', random.randint(1, 100))
page_size = kwargs.get('page_size', 20)
kwargs.update({'page_number': page_number, 'page_size': page_size})
# 模糊查询字段
_name_likes = {
cls.trans_info.key: '%{}%',
cls.opinion.key: '%{}%',
}
_query = select(cls).where(
*cls.search_wheres(likes=_name_likes, **kwargs)
).group_by(cls.id)
_paging = None
if is_paging:
_row_count = await cls.query_count(_query)
_paging = Pagination(_row_count).paging(page_number, page_size)
_data_query = _query.limit(page_size).offset(_paging.offset_size)
else:
_data_query = _query.where()
_sort_clause = cls.sort_clauses(kwargs.get('sort_clause', {}))
if _sort_clause:
_data_query = _data_query.order_by(*_sort_clause)
else:
_data_query = _data_query.order_by(cls.task_number, cls.rec_id)
_dispose_df = await cls.query_as_df(_data_query)
if not _dispose_df.empty:
_dispose_df.replace(models.EmptyInDF + models.EmptyDatetimeInDF, '', inplace=True)
_dispose_df[cls.id.key] = _dispose_df[cls.id.key].astype(str)
return _dispose_df, _paging
@classmethod
async def search(cls, **kwargs):
"""
按参数搜索批转任务数据,返回分页格式数据。
"""
_dispose_df, _paging = await cls.search_base(**kwargs)
return {
'total': _paging.row_count,
'rows': _dispose_df.to_dict('records'),
'pagination': {
'page_number': _paging.page_number,
'page_count': _paging.page_count,
'page_size': _paging.page_size,
},
}
@classmethod
async def exists_rec_id(cls, data_df: pd.DataFrame):
"""
查找 data_df 中在数据库中已存在和不存在的记录。根据 rec_id 和 task_number 判断。
:param data_df: 输入的数据框架,必须包含 rec_id 和 task_number 列
:return: (exists_df: pd.DataFrame, latest_df: pd.DataFrame)
- exists_df: 在数据库中存在的记录
- latest_df: 在数据库中不存在的记录
"""
if data_df.empty:
return pd.DataFrame(), pd.DataFrame()
# 获取待查询的 rec_id 和 task_number 列表(去重组合)
rec_ids = data_df[cls.rec_id.key].unique().tolist()
task_numbers = data_df[cls.task_number.key].unique().tolist()
if not rec_ids and not task_numbers:
return pd.DataFrame(), data_df.copy()
# 查询数据库中已存在的记录(任一匹配)
_query = select(cls.id, cls.rec_id, cls.task_number).where(
(cls.rec_id.in_(rec_ids)) | (cls.task_number.in_(task_numbers))
)
exists_df = await cls.query_as_df(_query)
if exists_df.empty:
return pd.DataFrame(), data_df.copy()
# 构建 (rec_id, task_number) -> id 的映射字典
exists_map = set(zip(exists_df[cls.rec_id.key], exists_df[cls.task_number.key]))
# 标记是否存在
mask_exists = data_df.apply(
lambda row: (row[cls.rec_id.key], row[cls.task_number.key]) in exists_map,
axis=1
)
exists_df = data_df[mask_exists].copy()
latest_df = data_df[~mask_exists].copy()
# 为存在的记录补充 id 字段(可选)
exists_df[cls.id.key] = exists_df.apply(
lambda row: exists_df[
(exists_df[cls.rec_id.key] == row[cls.rec_id.key]) &
(exists_df[cls.task_number.key] == row[cls.task_number.key])
][cls.id.key].iloc[0] if len(exists_df[
(exists_df[cls.rec_id.key] == row[cls.rec_id.key]) &
(exists_df[cls.task_number.key] == row[cls.task_number.key])
]) > 0 else None,
axis=1
)
return exists_df, latest_df
@register_swagger_model
class DcmDispose(DcmDisposeBase):
"""
批转任务模型类(主业务类,完全继承 TD3iDcmDispose 字段)。
---
description: 数字城管-批转接口
type: object
properties:
id:
description: 主键ID
type: integer
example: 1001
readOnly: true
rec_id:
description: 记录ID
type: string
example: "20240501001"
maxLength: 64
task_number:
description: 任务号
type: string
example: "TASK20240501001"
maxLength: 64
act_id:
description: 工单ID
type: string
example: "ACT20240501001"
maxLength: 64
task_list_id:
description: 任务列表ID
type: string
example: "LIST20240501001"
maxLength: 64
trans_info:
description: 批转对象(固定:市受理员)
type: string
example: "市受理员"
maxLength: 64
opinion:
description: 批转意见
type: string
example: "请转交至市容科处理"
maxLength: 65535
add_num:
description: 批转意见(冗余字段)
type: string
example: "请转交"
maxLength: 32
attachments:
description: 附件(JSON格式)
type: string
example: '["file1.jpg","file2.pdf"]'
maxLength: 65535
send_message:
description: 发送短信(1:发送,0:不发送)
type: string
example: "1"
maxLength: 32
status:
description: 提交状态
type: integer
example: 1
created_at:
description: 创建时间,ISO格式的日期时间字符串
type: string
format: date-time
example: "2024-01-15 10:30:00"
readOnly: true
created_by:
description: 创建者用户名
type: string
example: "admin"
readOnly: true
updated_at:
description: 修改时间,ISO格式的日期时间字符串
type: string
format: date-time
example: "2024-01-16 14:25:00"
readOnly: true
updated_by:
description: 修改者用户名
type: string
example: "editor"
readOnly: true
"""
@classmethod
async def create(cls, user: RbacUser = None, **kwargs):
"""
创建新的批转任务。
业务流程:
1. 使用 TD3iDcmDisposeForm 验证表单数据完整性
2. 检查是否存在相同记录ID或任务号的批转记录
3. 创建新批转对象
4. 设置创建者和更新者为当前用户
5. 保存到数据库
6. 返回创建的批转对象
:param RbacUser user: 操作用户对象
:param kwargs: 批转参数字典
:return: 新建批转任务对象
:rtype: TD3iDcmDispose
:raises AssertionError: 当记录已存在时抛出
:raises ValidationError: 当表单验证失败时抛出
"""
# 处理字符串字段去除空格
for _k, _v in kwargs.items():
if isinstance(_v, str):
kwargs[_k] = _v.strip()
_dispose_form = DcmDisposeForm(formdata=kwargs)
_dispose_form.validate_form()
# 检查是否已存在相同记录ID或任务号
_exist: cls = await cls.is_exist(_dispose_form.rec_id.data, _dispose_form.task_number.data)
assert _exist is None, "该记录ID或任务号已存在批转记录,不能重复创建。"
# 创建批转对象
_dispose = cls().copy_from_dict(_dispose_form.data, skip_none=True).before_save()
if user:
_dispose.created_by = user.username
_dispose.updated_by = user.username
await _dispose.async_save()
return _dispose
@classmethod
async def delete(cls, dispose_id: Union[str, int]):
"""
删除批转任务。
业务流程:
1. 根据ID查找批转任务
2. 验证任务存在性
3. 执行删除操作
:param dispose_id: 要删除的批转任务ID
:return: 删除的批转任务对象
:rtype: TD3iDcmDispose
:raises AssertionError: 当任务不存在时抛出
"""
_dispose: cls = await cls.async_find_by_id(dispose_id)
assert _dispose, f"根据 ID {dispose_id} 未找到批转任务。"
# 执行删除
_del_query = delete(cls).where(cls.id == _dispose.id)
_del_count = (await cls.raw_execute(_del_query)).rowcount
echo_log(f'已删除批转任务(任务号:{_dispose.task_number}ID{_dispose.id}.')
return _dispose
@classmethod
async def modify(cls, dispose_id: Union[str, int], user: RbacUser = None, **kwargs):
"""
修改已有批转任务信息。
业务流程:
1. 将 dispose_id 添加到参数中
2. 处理字符串字段去除首尾空格
3. 使用 TD3iDcmDisposeForm 验证表单数据
4. 检查是否有其他批转任务使用了相同的 rec_id 或 task_number
5. 查询原批转任务对象
6. 验证任务存在性
7. 更新字段并设置更新者
8. 保存到数据库
9. 返回更新后的批转任务对象
:param dispose_id: 要修改的批转任务ID
:param RbacUser user: 操作用户对象
:param kwargs: 需要更新的字段
:return: 修改后的批转任务对象
:rtype: TD3iDcmDispose
:raises AssertionError: 当任务不存在或信息重复时抛出
:raises ValidationError: 当表单验证失败时抛出
"""
# 处理字符串字段去除空格
for _k, _v in kwargs.items():
if isinstance(_v, str):
kwargs[_k] = _v.strip()
# 表单验证
_dispose_form = DcmDisposeForm(formdata=kwargs)
_dispose_form.validate_form()
# 检查是否与其他批转任务重复(排除自身)
_other = await cls.exist_other(
dispose_id,
_dispose_form.rec_id.data,
_dispose_form.task_number.data
)
assert _other is None, "批转记录ID或任务号已存在,不能重复修改。"
# 查询原批转任务
_dispose: cls = await cls.async_find_by_id(dispose_id)
assert _dispose, f'查无此批转信息。'
# 更新字段
_dispose.copy_from_dict(_dispose_form.data, skip_none=True).before_save()
_dispose.updated_by = user.username
await _dispose.async_save()
return _dispose
@classmethod
async def create_batch(cls, data_df: pd.DataFrame, user: RbacUser = None):
"""
批量创建新批转任务(传入数据应为全新记录,无需校验是否存在)。
:param data_df: 包含批转任务数据的 DataFrame,字段需与模型属性匹配(如 rec_id, task_number 等)
:param user: 操作用户对象,用于设置 created_by / updated_by
:return: 成功创建的任务数量
:rtype: int
"""
if data_df.empty:
return 0
# 向量化设置用户字段(无循环)
if user:
data_df['created_by'] = user.username
data_df['updated_by'] = user.username
# 一次性转为字典列表(C 层高效)
records = data_df.to_dict('records')
# 用列表推导式构造对象
disposals = [cls().copy_from_dict(record, skip_none=True).before_save() for record in records]
# 批量插入
session = cls.get_aio_session()
try:
session.add_all(disposals)
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(disposals)} 条新批转记录。")
return len(disposals)
@classmethod
async def modify_batch(cls, data_df: pd.DataFrame, user: RbacUser = None):
"""
批量修改已有批转任务。
:param data_df: 包含批转任务数据的 DataFrame,必须包含 id 列
:param user: 操作用户对象,用于设置 updated_by
:return: 成功更新的任务数量
: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
# 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
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} 条批转记录。")
return updated_count
@classmethod
async def save_batch(cls, data_df: pd.DataFrame, user: RbacUser = None):
"""
批量保存数据,自动处理新建和更新。
:param data_df: 要保存的数据框架
:param user: 用户
:return: 新建和更新的数量
"""
# 筛选数据状态
_exists_df, _latest_df = await DcmDispose.exists_rec_id(data_df)
# 保存到数据库
_created_count = await DcmDispose.create_batch(_latest_df, user)
_updated_count = await DcmDispose.modify_batch(_exists_df, user)
return _created_count, _updated_count