Files
d3i-szct/models/govc_task_process.py
2026-06-02 17:46:38 +08:00

519 lines
19 KiB
Python
Raw Permalink Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
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, DateTimeField
from wtforms.validators import Length, Optional
import models
from models.common_model import CommonModel
from models.db_models import TD3iGovcTaskProces
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 GovcTaskProcessForm(ModelForm):
"""
工单流程追踪表单验证类(完全映射 TD3iGovcTaskProcess 字段)。
用于验证和处理市12345工单流程追踪的创建/修改表单数据。
字段完全映射数据库表 t_d3i_govc_task_process 的字段结构。
"""
# 基础信息
id = IntegerField('记录ID')
task_id = IntegerField('关联工单主表ID', validators=[Optional()])
handle_time = DateTimeField('办理时间', validators=[Optional()])
operate_status = StringField('办理状态', validators=[Length(max=128, message='办理状态长度不能超过128字符')])
activity_guid = StringField('办理环节名称', validators=[Length(max=255, message='办理环节名称长度不能超过255字符')])
handle_opinion = TextAreaField('办理意见')
is_finish = IntegerField('是否结束')
operator_ou_name = StringField('部门', validators=[Length(max=255, message='部门长度不能超过255字符')])
is_back = IntegerField('是否回退')
operator_name = StringField('办理人', validators=[Length(max=128, message='办理人长度不能超过128字符')])
created_at = DateTimeField('创建时间', validators=[Optional()])
created_by = StringField('创建者', validators=[Length(max=64, message='创建者长度不能超过64字符')])
updated_at = DateTimeField('更新时间', validators=[Optional()])
updated_by = StringField('更新者', validators=[Length(max=64, message='更新者长度不能超过64字符')])
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 GovcTaskProcessBase(TD3iGovcTaskProces, CommonModel):
"""
工单流程追踪基础类(完全映射 TD3iGovcTaskProcess 字段)。
继承自数据库模型 TD3iGovcTaskProcess 和通用模型 CommonModel。
封装所有与工单流程追踪相关的通用操作方法。
"""
FieldMapping = {
'id': 'id',
'task_id': 'task_id',
'handle_time': 'handle_time',
'operate_status': 'operate_status',
'activity_guid': 'activity_guid',
'handle_opinion': 'handle_opinion',
'is_finish': 'is_finish',
'operator_ou_name': 'operator_ou_name',
'is_back': 'is_back',
'operator_name': 'operator_name',
'created_at': 'created_at',
'created_by': 'created_by',
'updated_at': 'updated_at',
'updated_by': 'updated_by',
}
"""
工单流程追踪数据映射
"""
@classmethod
async def is_exist(cls, task_id: int, activity_guid: str):
"""
检查工单流程记录是否已存在(根据工单ID+办理环节名称)。
:param task_id: 关联工单主表ID
:param activity_guid: 办理环节名称
:return: 存在返回对象,不存在返回None
"""
_query = select(cls).where(
cls.task_id == task_id,
cls.activity_guid == activity_guid
)
_process: cls = await cls.query_first(_query)
return _process
@classmethod
async def search_base(cls, is_paging=True, **kwargs):
"""
按参数搜索工单流程追踪数据的基础方法。
支持字段:
- task_id, operate_status, is_finish, is_back, operator_name
- 支持模糊匹配:activity_guid, handle_opinion, operator_ou_name
- 支持精确匹配:task_id, is_finish, is_back
: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 {'handle_time': 'desc'}
:key int task_id: 精确匹配关联工单主表ID
:key str operate_status: 精确匹配办理状态
:key str activity_guid: 模糊匹配办理环节名称
:key str handle_opinion: 模糊匹配办理意见
:key int is_finish: 精确匹配是否结束
:key str operator_ou_name: 模糊匹配部门
:key int is_back: 精确匹配是否回退
:key str operator_name: 精确匹配办理人
: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.activity_guid.key: '%{}%',
cls.handle_opinion.key: '%{}%',
cls.operator_ou_name.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_id, cls.handle_time.desc())
_process_df = await cls.query_as_df(_data_query)
if not _process_df.empty:
_process_df.replace(models.EmptyInDF + models.EmptyDatetimeInDF, '', inplace=True)
_process_df[cls.id.key] = _process_df[cls.id.key].astype(str)
_process_df[cls.task_id.key] = _process_df[cls.task_id.key].astype(str)
return _process_df, _paging
@classmethod
async def search(cls, **kwargs):
"""
按参数搜索工单流程追踪数据,返回分页格式数据。
"""
_process_df, _paging = await cls.search_base(**kwargs)
return {
'total': _paging.row_count,
'rows': _process_df.to_dict('records'),
'pagination': {
'page_number': _paging.page_number,
'page_count': _paging.page_count,
'page_size': _paging.page_size,
},
}
@classmethod
async def exists_task_activity(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 task_id + activity_guid 判断。
:param data_df: 输入的数据框架,必须包含 task_id 和 activity_guid 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()
# 校验必要列
required_cols = [cls.task_id.key, cls.activity_guid.key]
if not all(col in data_df.columns for col in required_cols):
echo_log(f"错误:exists_task_activity 要求输入数据必须包含 {required_cols}")
return pd.DataFrame(), data_df.copy()
# 构建 task_id+activity_guid 组合键
data_df['_combine_key'] = data_df[cls.task_id.key].astype(str) + '|' + data_df[
cls.activity_guid.key].str.strip()
# 获取待查询的组合键列表(去重)
combine_keys = data_df['_combine_key'].unique().tolist()
if not combine_keys:
return pd.DataFrame(), data_df.copy()
# 查询数据库中已存在的记录
_query = select(cls.id, cls.task_id, cls.activity_guid)
_process_df = await cls.query_as_df(_query)
if _process_df.empty:
data_df.drop(columns=['_combine_key'], inplace=True)
return pd.DataFrame(), data_df.copy()
# 构建数据库组合键
_process_df['_combine_key'] = _process_df[cls.task_id.key].astype(str) + '|' + _process_df[
cls.activity_guid.key].str.strip()
combine_key_to_id_map = dict(zip(_process_df['_combine_key'], _process_df[cls.id.key]))
# 根据组合键划分数据
mask_exists = data_df['_combine_key'].isin(_process_df['_combine_key'])
exists_df = data_df[mask_exists].copy()
# 自动补充从数据库查到的 id 字段
exists_df[cls.id.key] = exists_df['_combine_key'].map(combine_key_to_id_map)
latest_df = data_df[~mask_exists].copy()
# 清理临时列
for df in [exists_df, latest_df, data_df]:
if '_combine_key' in df.columns:
df.drop(columns=['_combine_key'], inplace=True)
return exists_df, latest_df
@register_swagger_model
class GovcTaskProcess(GovcTaskProcessBase):
"""
工单流程追踪模型类(主业务类,完全继承 TD3iGovcTaskProcess 字段)。
---
description: 市12345工单流程追踪接口
type: object
properties:
id:
description: 主键ID
type: integer
example: 1001
readOnly: true
task_id:
description: 关联工单主表ID
type: integer
example: 5001
handle_time:
description: 办理时间
type: string
format: date-time
example: "2024-01-15 10:30:00"
operate_status:
description: 办理状态
type: string
example: "处理中"
maxLength: 128
activity_guid:
description: 办理环节名称
type: string
example: "市级受理"
maxLength: 255
handle_opinion:
description: 办理意见
type: string
example: "已接收工单,正在分派处理"
is_finish:
description: 是否结束(0:未结束,1:已结束)
type: integer
example: 0
operator_ou_name:
description: 部门
type: string
example: "市12345政务服务中心"
maxLength: 255
is_back:
description: 是否回退(0:否,1:是)
type: integer
example: 0
operator_name:
description: 办理人
type: string
example: "张三"
maxLength: 128
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: "system"
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):
"""
创建新的工单流程追踪记录。
业务流程:
1. 使用 GovcTaskProcessForm 验证表单数据完整性
2. 检查是否已存在相同 task_id+activity_guid 的记录(避免重复提交)
3. 创建新流程追踪对象
4. 设置创建者和更新者为当前用户
5. 保存到数据库
6. 返回创建的对象
:param RbacUser user: 操作用户对象
:param kwargs: 工单流程追踪参数字典
:return: 新建流程追踪对象
:rtype: GovcTaskProcess
: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()
_form = GovcTaskProcessForm(formdata=kwargs)
_form.validate_form()
# 检查是否已存在相同 task_id+activity_guid 的记录
_existing = await cls.is_exist(_form.task_id.data, _form.activity_guid.data)
assert _existing is None, f"工单ID {_form.task_id.data}{_form.activity_guid.data} 环节记录已存在,不能重复提交。"
# 创建对象
_process = cls().copy_from_dict(_form.data, skip_none=True).before_save()
if user:
_process.created_by = user.username
_process.updated_by = user.username
await _process.async_save()
return _process
@classmethod
async def delete(cls, process_id: Union[str, int]):
"""
删除工单流程追踪记录。
业务流程:
1. 根据ID查找记录
2. 验证存在性
3. 执行删除
:param process_id: 要删除的流程追踪记录ID
:return: 删除的记录对象
:rtype: GovcTaskProcess
:raises AssertionError: 当记录不存在时抛出
"""
_process: cls = await cls.async_find_by_id(process_id)
assert _process, f"根据 ID {process_id} 未找到工单流程追踪记录。"
_del_query = delete(cls).where(cls.id == _process.id)
_del_count = (await cls.raw_execute(_del_query)).rowcount
echo_log(f'已删除工单流程追踪记录(工单ID{_process.task_id},环节:{_process.activity_guid}ID{_process.id}.')
return _process
@classmethod
async def modify(cls, process_id: Union[str, int], user: RbacUser = None, **kwargs):
"""
修改已有工单流程追踪记录。
业务流程:
1. 将 process_id 添加到参数中
2. 处理字符串字段去除首尾空格
3. 使用 GovcTaskProcessForm 验证表单数据
4. 查询原记录
5. 验证存在性
6. 更新字段并设置更新者
7. 保存到数据库
8. 返回更新后的对象
:param process_id: 要修改的流程追踪记录ID
:param RbacUser user: 操作用户对象
:param kwargs: 需要更新的字段
:return: 修改后的流程追踪对象
:rtype: GovcTaskProcess
:raises AssertionError: 当记录不存在时抛出
: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()
# 表单验证
_form = GovcTaskProcessForm(formdata=kwargs)
_form.validate_form()
# 查询原记录
_process: cls = await cls.async_find_by_id(process_id)
assert _process, f'查无此工单流程追踪信息(ID{process_id})。'
# 更新字段
_process.copy_from_dict(_form.data, skip_none=True).before_save()
if user:
_process.updated_by = user.username
await _process.async_save()
return _process
@classmethod
async def create_batch(cls, data_df: pd.DataFrame, user: RbacUser = None):
"""
批量创建工单流程追踪记录(传入数据应为全新记录)。
:param data_df: 包含流程追踪数据的 DataFrame
:param user: 操作用户对象,用于设置 created_by / updated_by
:return: 成功创建的数量
:rtype: int
"""
if data_df.empty:
return 0
# 设置创建者/更新者信息
current_time = datetime.datetime.now()
if user:
data_df['created_by'] = user.username
data_df['updated_by'] = user.username
# 补充默认时间字段
data_df['created_at'] = data_df.get('created_at', current_time)
data_df['updated_at'] = data_df.get('updated_at', current_time)
records = data_df.to_dict('records')
processes = [cls().copy_from_dict(record, skip_none=True).before_save() for record in records]
session = cls.get_aio_session()
try:
session.add_all(processes)
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(processes)} 条工单流程追踪记录。")
return len(processes)
@classmethod
async def modify_batch(cls, data_df: pd.DataFrame, user: RbacUser = None):
"""
批量修改已有工单流程追踪记录。
:param data_df: 包含流程追踪数据的 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 cls.id.key 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和更新者
data_df['updated_at'] = datetime.datetime.now()
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} 条工单流程追踪记录。")
return updated_count
@classmethod
async def save_batch(cls, data_df: pd.DataFrame, user: RbacUser = None):
"""
批量保存工单流程追踪数据,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(根据 task_id + activity_guid 判断是否已存在)
_exists_df, _latest_df = await cls.exists_task_activity(data_df)
# 保存到数据库
_created_count = await cls.create_batch(_latest_df, user)
_updated_count = await cls.modify_batch(_exists_df, user)
return _created_count, _updated_count