zwf
261 lines
11 KiB
Python
261 lines
11 KiB
Python
"""
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待办工单办理过程推送。
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对应文档接口：5、推送工单处理流程列表
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"""
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import asyncio
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import io
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import json
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from typing import Optional, Union
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import pandas as pd
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from sqlalchemy import select, desc
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from tornado.httpclient import HTTPResponse, HTTPRequest
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import dock
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import models
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from dock.oa import oa_api_request
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from dock.govs import govs_download_file
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from models.govs_order_master import GovsOrderMaster
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from models.govs_order_process import GovsOrderProcess
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from models.govs_push_status import GovsPushStatus
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from paste.core.logging import echo_log
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from paste.util import udict
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from paste.web import requests
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GovsOrderProcessMapping = {
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GovsOrderProcess.id.key: 'id',
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GovsOrderProcess.master_id.key: 'parentId',
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GovsOrderProcess.action_name.key: 'processingSteps',
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GovsOrderProcess.handler_org_names.key: 'processingDepartment',
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GovsOrderProcess.handler_user_names.key: 'processor',
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GovsOrderProcess.deal_type.key: 'processingMethod',
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GovsOrderProcess.next_org_names.key: 'receivingDepartment',
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GovsOrderProcess.next_handler_user_names.key: 'receiver',
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GovsOrderProcess.adv_content.key: 'processingOpinion',
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GovsOrderProcess.deal_date.key: 'processingTime',
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GovsOrderProcess.plan_finish_time.key: 'plannedCompletionTime',
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GovsOrderProcess.remarks.key: 'remarks',
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GovsOrderProcess.attachment_dto_list.key: 'fileIdList'
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}
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"""
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数据推送映射关系。
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"""
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async def after_push_order_process_request(response: HTTPResponse, retry_queue: asyncio.Queue[HTTPRequest]):
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"""
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工单推送请求响应后的处理程序。
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:param response: 响应对象
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:param retry_queue: 重试队列
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"""
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body = response.body.decode()
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echo_log(body)
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body_data = json.loads(body)
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code = udict.get_by_path(body_data, 'code')
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message = udict.get_by_path(body_data, 'msg')
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if code == 200:
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govs_task_id = getattr(response.request, "govs_task_id")
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await GovsPushStatus.set_push_order_process_status(govs_task_id)
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echo_log(f"推送工单办理过程成功.")
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else:
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echo_log(f"推送工单办理过程失败：{message}")
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if retry_queue:
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echo_log(f"工单办理过程重试队列中有：{retry_queue.qsize()} 个请求在等待.")
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async def done_push_order_process(response_list: list[HTTPResponse]):
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"""
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推送完成工单办理过程后的回调
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"""
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unique_task_ids = set()
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for response in response_list:
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task_id = getattr(response.request, 'govs_task_id', None)
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if task_id:
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unique_task_ids.add(task_id)
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return unique_task_ids
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async def done_attachment_download(response_list: list[HTTPResponse]):
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"""
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所有附件下载完成执行的处理程序。
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:param response_list: 附件下载响应列表
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:return: 返回附件字典列表，每个元素包含文件名和io对象
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"""
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downloaded_attachments = []
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for response in response_list:
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file_name = getattr(response.request, "file_name", "file")
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file_io = io.BytesIO(response.body)
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downloaded_attachments.append({
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"file_name": file_name, "file_io": file_io
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})
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return downloaded_attachments
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async def done_attachment_upload(response_list: list[HTTPResponse]):
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"""
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所有附件上传到OA完成后执行的处理程序
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:param response_list: 附件下载响应列表
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:return: 返回文件id列表
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"""
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file_ids = []
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for response in response_list:
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body = response.body.decode()
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echo_log(body)
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body_data = json.loads(body)
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nas = udict.get_by_path(body_data, 'n_a_s')
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if nas:
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oa_media_id = body_data.get('atts', [])[0].get('fileUrl')
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file_ids.append(oa_media_id)
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echo_log(f"省12345的办理过程的附件上传成功.")
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else:
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echo_log(f"省12345的办理过程的附件上传失败.")
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return file_ids
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async def download_and_upload_attachment(attachment_list: list):
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"""
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从省12345下载附件，并上传到OA
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:param attachment_list: 附件信息列表
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:return: 返回上传OA成功的文件id列表
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"""
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download_queue = asyncio.Queue()
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for attachment in attachment_list:
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download_request = await govs_download_file.get_download_request('1773611023340371969', attachment['filePath'])
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setattr(download_request, 'file_name', attachment['attachName'])
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await download_queue.put(download_request)
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downloaded_attachments = await requests.async_concurrency(download_queue, con_count=dock.CONCURRENCY_COUNT,
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retry=dock.MAX_RETRY_COUNT,
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after_done=done_attachment_download)
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oa_upload_queue = asyncio.Queue()
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for downloaded_attachment in downloaded_attachments:
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upload_request = await oa_api_request.get_upload_request(downloaded_attachment['file_io'],
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downloaded_attachment['file_name'], False)
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await oa_upload_queue.put(upload_request)
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uploaded_attachment_ids = await requests.async_concurrency(oa_upload_queue, con_count=dock.CONCURRENCY_COUNT,
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retry=dock.MAX_RETRY_COUNT,
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after_done=done_attachment_upload)
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return uploaded_attachment_ids
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async def push_order_process(fetch_size: int = 50,
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task_id: Optional[Union[str, int, list[Union[str, int]]]] = None):
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"""
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推送12345工单办理过程。
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:param fetch_size: 本次推送数量
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:param task_id: 待办任务 ID 可选
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"""
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# 根据条件获取目标任务 ID 列表（支持指定 task_id 或分页获取）
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task_query = select(GovsOrderMaster.id).order_by(desc(GovsOrderMaster.id))
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if task_id is not None:
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if isinstance(task_id, list):
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task_query = task_query.where(GovsOrderMaster.id.in_(task_id))
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echo_log(f"本次推送待办列表：{task_id} 的详细数据...")
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else:
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task_query = task_query.where(GovsOrderMaster.id == task_id)
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echo_log(f"本次推送待办：{task_id} 的详细数据...")
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else:
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task_query = task_query.limit(fetch_size)
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echo_log(f"本次推送前 {fetch_size} 条待办的详细数据...")
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govs_task_df = await GovsOrderProcess.query_as_df(task_query)
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# 预处理数据方法
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def preprocess(df: pd.DataFrame):
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# 格式化为字符串
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df[GovsOrderProcess.id.key] = df[GovsOrderProcess.id.key].astype(str)
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df[GovsOrderProcess.master_id.key] = df[GovsOrderProcess.master_id.key].astype(
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str)
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# 日期转换为字符串
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df[GovsOrderProcess.deal_date.key] = df[GovsOrderProcess.deal_date.key].apply(
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lambda x: x.strftime('%Y-%m-%d %H:%M:%S') if pd.notna(x) and hasattr(x, 'strftime') else ''
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)
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df[GovsOrderProcess.plan_finish_time.key] = df[GovsOrderProcess.plan_finish_time.key].apply(
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lambda x: x.strftime('%Y-%m-%d %H:%M:%S') if pd.notna(x) and hasattr(x, 'strftime') else ''
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)
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# 更名，并仅保留需要的列
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df = df.rename(columns=GovsOrderProcessMapping)
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df = df[list(GovsOrderProcessMapping.values())]
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df[GovsOrderProcess.master_id.key] = df['parentId']
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return df
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# 填充处理过程
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await GovsOrderProcess.fill_process_info(govs_task_df, column_name='processLogBOList', preprocessing=preprocess)
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# 处理无待办工单处理过程状态
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empty_govs_task_df = govs_task_df[govs_task_df['processLogBOList'].apply(lambda x: len(x) == 0)]
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empty_govs_task_df[GovsPushStatus.master_id.key] = empty_govs_task_df[GovsOrderMaster.id.key]
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empty_govs_task_df[GovsPushStatus.push_order_process_status.key] = 1
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empty_govs_task_df = empty_govs_task_df[
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[GovsPushStatus.master_id.key, GovsPushStatus.push_order_process_status.key]]
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await GovsPushStatus.save_batch(empty_govs_task_df)
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# 过滤空数组
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full_govs_task_df = govs_task_df[govs_task_df['processLogBOList'].apply(lambda x: len(x) > 0)]
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# 删除 processLogBOList内的工单id字段
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def remove_govs_task_id(data_list):
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for item in data_list:
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if isinstance(item, dict) and GovsOrderProcess.master_id.key in item:
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del item[GovsOrderProcess.master_id.key]
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return data_list
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# 执行替换
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full_govs_task_df['processLogBOList'] = full_govs_task_df['processLogBOList'].apply(remove_govs_task_id)
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# 处理数据映射，适应接口推送
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mapped_df = full_govs_task_df.rename(columns={GovsOrderMaster.id.key: 'gdId'})
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mapped_df['gdId'] = mapped_df['gdId'].astype(str)
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# 这里把空数据都换成 None，以便存入数据库时是 null
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mapped_df.replace(models.EmptyInDF + models.EmptyDatetimeInDF, '', inplace=True)
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echo_log(f"正在准备请求队列...")
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# 构建请求队列
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push_queue = asyncio.Queue()
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# 向队列中填充请求对象
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for _h, row in mapped_df.iterrows():
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row_data = row.to_dict()
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process_list = row_data['processLogBOList']
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for i in range(len(process_list)):
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attachment_list = process_list[i].get('fileIdList')
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if not attachment_list:
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process_list[i]['fileIdList'] = []
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else:
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if isinstance(attachment_list, str):
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try:
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attachment_list = json.loads(attachment_list)
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# 从省12345下载附件，然后上传到OA，获取id列表
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oa_file_ids = await download_and_upload_attachment(attachment_list)
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process_list[i]['fileIdList'] = oa_file_ids
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except Exception as e:
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echo_log(f'下载省12345的附件并上传到OA时遇到错误：{e}', is_log_exc=True)
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process_list[i]['fileIdList'] = []
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else:
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process_list[i]['fileIdList'] = []
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push_request = await oa_api_request.get_push_gov_process_request(**row_data)
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setattr(push_request, "govs_task_id", row.get('gdId'))
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await push_queue.put(push_request)
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# 并发提交推送请求
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echo_log(f"开始推送待办过程数据...")
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pushed_task_ids = await requests.async_concurrency(
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push_queue, con_count=dock.CONCURRENCY_COUNT, retry=dock.MAX_RETRY_COUNT,
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after_request=after_push_order_process_request, after_done=done_push_order_process
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)
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echo_log(f"待办过程数据推送已经完成...")
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return pushed_task_ids
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if __name__ == "__main__":
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from paste.core import aio_pool
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_runner = aio_pool.get_aio_runner()
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_runner(push_order_process(fetch_size=60))
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