初始化项目
This commit is contained in:
zwf
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"""
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待办工单附件数据上传。
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对应文档接口：7、推送附件信息
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"""
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import asyncio
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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 models.dcm_push_status import DcmPushStatus
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from models.dcm_task import DcmTask
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from models.dcm_task_attachment import DcmTaskAttachment
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from models.dcm_task_file_upload import DcmTaskFileUpload
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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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DcmTaskAttachmentMapping = {
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DcmTaskAttachment.id.key: 'id',
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DcmTaskFileUpload.oa_media_id.key: 'mediaId',
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DcmTaskAttachment.media_usage.key: 'mediaUsage',
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DcmTaskAttachment.act_def_name.key: 'actDefName',
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DcmTaskAttachment.upload_time.key: 'uploadCreateTime',
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}
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"""
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附件数据推送映射关系。
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"""
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async def after_push_attachment_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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dcm_task_id = getattr(response.request, "dcm_task_id")
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await DcmPushStatus.set_push_task_attachment_status(dcm_task_id)
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echo_log(f"推送企业待办附件成功.")
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else:
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echo_log(f"推送企业待办附件失败：{message}")
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if retry_queue:
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echo_log(f"企业待办附件重试队列中有：{retry_queue.qsize()} 个请求在等待.")
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async def push_attachment(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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推送待办附件数据及其数据。
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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(DcmTask.id).order_by(desc(DcmTask.act_id))
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if task_id:
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if isinstance(task_id, list):
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task_query = task_query.where(DcmTask.id.in_(task_id))
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echo_log(f"本次推送待办列表：{task_id} 的附件数据...")
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else:
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task_query = task_query.where(DcmTask.id == task_id)
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echo_log(f"本次推送待办：{task_id} 的附件数据...")
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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} 条待办附件数据...")
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dcm_task_df = await DcmTask.query_as_df(task_query)
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# 格式化为字符串
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dcm_task_df[DcmTask.id.key] = dcm_task_df[DcmTask.id.key].astype(str)
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# 预处理数据方法
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def preprocess(df: pd.DataFrame):
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# 更名，并仅保留需要的列
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df = df.rename(columns=DcmTaskAttachmentMapping)
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df = df[list(DcmTaskAttachmentMapping.values()) + [DcmTaskAttachment.dcm_task_id.key]]
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return df
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# 填充附件数据
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await DcmTaskAttachment.fill_attachment(dcm_task_df, column_name='attachmentList', preprocessing=preprocess)
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# 处理无附件待办状态
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empty_dcm_task_df = dcm_task_df[dcm_task_df['attachmentList'].apply(lambda x: len(x) == 0)]
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empty_dcm_task_df[DcmPushStatus.dcm_task_id.key] = empty_dcm_task_df[DcmTask.id.key]
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empty_dcm_task_df[DcmPushStatus.push_task_attachment_status.key] = 1
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empty_dcm_task_df = empty_dcm_task_df[[DcmPushStatus.dcm_task_id.key, DcmPushStatus.push_task_attachment_status.key]]
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await DcmPushStatus.save_batch(empty_dcm_task_df)
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# 过滤空数组
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full_dcm_task_df = dcm_task_df[dcm_task_df['attachmentList'].apply(lambda x: len(x) > 0)]
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# 删除 DcmTaskAttachment.dcm_task_id.key 字段
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def remove_dcm_task_id(attachment_list):
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for item in attachment_list:
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if isinstance(item, dict) and DcmTaskAttachment.dcm_task_id.key in item:
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del item[DcmTaskAttachment.dcm_task_id.key]
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return attachment_list
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# 执行替换
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full_dcm_task_df['attachmentList'] = full_dcm_task_df['attachmentList'].apply(remove_dcm_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_dcm_task_df.rename(columns={DcmTask.id.key: 'gdId'})
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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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dcm_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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push_request = await oa_api_request.get_push_attachment_request(**row.to_dict())
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setattr(push_request, "dcm_task_id", row.get('gdId'))
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await dcm_push_queue.put(push_request)
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# 并发提交推送请求
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echo_log(f"开始推送待办附件数据...")
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await requests.async_concurrency(
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dcm_push_queue, con_count=dock.CONCURRENCY_COUNT, retry=dock.MAX_RETRY_COUNT,
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after_request=after_push_attachment_request
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)
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echo_log(f"待办附件数据推送已经完成...")
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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_attachment(task_id=2054174091237265408))
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@@ -0,0 +1,135 @@
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"""
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待办工单扩展数据推送。
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对应文档接口：9、推送扩展信息
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"""
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import asyncio
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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 models.dcm_push_status import DcmPushStatus
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from models.dcm_task import DcmTask
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from models.dcm_task_extend_info import DcmTaskExtendedInfo
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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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DcmTaskExtendedInfoMapping = {
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DcmTaskExtendedInfo.id.key: 'id',
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DcmTaskExtendedInfo.display_name.key: 'fieldName',
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DcmTaskExtendedInfo.field_value.key: 'fieldValue'
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}
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async def after_push_extend_info_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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dcm_task_id = getattr(response.request, "dcm_task_id")
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await DcmPushStatus.set_push_task_extend_info_status(dcm_task_id)
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echo_log(f"推送企业待办扩展信息成功.")
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else:
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echo_log(f"推送企业待办扩展信息失败：{message}")
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if retry_queue:
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echo_log(f"企业待办扩展信息重试队列中有：{retry_queue.qsize()} 个请求在等待.")
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async def push_extend_info(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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推送待办扩展信息数据及其数据。
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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(DcmTask.id).order_by(desc(DcmTask.act_id))
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if task_id:
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if isinstance(task_id, list):
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task_query = task_query.where(DcmTask.id.in_(task_id))
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echo_log(f"本次推送待办列表：{task_id} 的扩展信息数据...")
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else:
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task_query = task_query.where(DcmTask.id == task_id)
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echo_log(f"本次推送待办：{task_id} 的扩展信息数据...")
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else:
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task_query = task_query.limit(fetch_size)
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echo_log(f"本次推送待办前 {fetch_size} 条扩展信息数据...")
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dcm_task_df = await DcmTask.query_as_df(task_query)
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# 格式化为字符串
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dcm_task_df[DcmTask.id.key] = dcm_task_df[DcmTask.id.key].astype(str)
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# 预处理数据方法
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def preprocess(df: pd.DataFrame):
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# 更名，并仅保留需要的列
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df = df.rename(columns=DcmTaskExtendedInfoMapping)
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df = df[list(DcmTaskExtendedInfoMapping.values())+[DcmTaskExtendedInfo.dcm_task_id.key]]
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return df
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# 填充表单数据
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await DcmTaskExtendedInfo.fill_extend_info(dcm_task_df, column_name='extendList', preprocessing=preprocess)
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# 处理无待办工单扩展信息状态
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empty_dcm_task_df = dcm_task_df[dcm_task_df['extendList'].apply(lambda x: len(x) == 0)]
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empty_dcm_task_df[DcmPushStatus.dcm_task_id.key] = empty_dcm_task_df[DcmTask.id.key]
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empty_dcm_task_df[DcmPushStatus.push_task_extend_info_status.key] = 1
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empty_dcm_task_df = empty_dcm_task_df[[DcmPushStatus.dcm_task_id.key, DcmPushStatus.push_task_extend_info_status.key]]
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await DcmPushStatus.save_batch(empty_dcm_task_df)
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# 过滤空数组
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full_dcm_task_df = dcm_task_df[dcm_task_df['extendList'].apply(lambda x: len(x) > 0)]
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# 删除 DcmTaskExtendedInfo.dcm_task_id.key 字段
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def remove_dcm_task_id(attachment_list):
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for item in attachment_list:
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if isinstance(item, dict) and DcmTaskExtendedInfo.dcm_task_id.key in item:
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del item[DcmTaskExtendedInfo.dcm_task_id.key]
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return attachment_list
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# 执行替换
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full_dcm_task_df['extendList'] = full_dcm_task_df['extendList'].apply(remove_dcm_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_dcm_task_df.rename(columns={DcmTask.id.key: 'gdId'})
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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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dcm_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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push_request = await oa_api_request.get_push_extend_info_request(**row.to_dict())
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setattr(push_request, "dcm_task_id", row.get('gdId'))
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await dcm_push_queue.put(push_request)
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# 并发提交推送请求
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echo_log(f"开始推送代办扩展信息数据...")
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await requests.async_concurrency(
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dcm_push_queue, con_count=dock.CONCURRENCY_COUNT, retry=dock.MAX_RETRY_COUNT,
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after_request=after_push_extend_info_request
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)
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echo_log(f"待办扩展信息推送已经完成...")
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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_extend_info(task_id=2054174091237265408))
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@@ -0,0 +1,139 @@
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"""
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待办工单更多信息推送。
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对应文档接口：8、推送更多信息
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"""
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import asyncio
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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 models.dcm_push_status import DcmPushStatus
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from models.dcm_task import DcmTask
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from models.dcm_task_more_info import DcmTaskMoreInfo
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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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DcmTaskMoreInfoMapping = {
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DcmTaskMoreInfo.id.key: 'id',
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DcmTaskMoreInfo.create_time.key: 'time'
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}
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"""
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表单数据-更多信息推送映射关系。
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"""
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async def after_push_more_info_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。
|
||||
|
||||
:param response: 响应对象
|
||||
:param retry_queue: 重试队列
|
||||
"""
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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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dcm_task_id = getattr(response.request, "dcm_task_id")
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await DcmPushStatus.set_push_task_more_info_status(dcm_task_id)
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echo_log(f"推送企业待办更多信息成功.")
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else:
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echo_log(f"推送企业待办更多信息失败：{message}")
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|
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if retry_queue:
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echo_log(f"企业待办更多信息重试队列中有：{retry_queue.qsize()} 个请求在等待.")
|
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async def push_more_info(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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推送待办更多信息数据及其数据。
|
||||
|
||||
:param fetch_size: 本次推送数量
|
||||
:param task_id: 待办任务 ID 可选
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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）
|
||||
task_query = select(DcmTask.id).order_by(desc(DcmTask.act_id))
|
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if task_id:
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if isinstance(task_id, list):
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task_query = task_query.where(DcmTask.id.in_(task_id))
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echo_log(f"本次推送待办列表：{task_id} 的更多信息数据...")
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||||
else:
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||||
task_query = task_query.where(DcmTask.id == task_id)
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echo_log(f"本次推送待办：{task_id} 的更多信息数据...")
|
||||
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} 条更多信息数据...")
|
||||
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dcm_task_df = await DcmTask.query_as_df(task_query)
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# 格式化为字符串
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||||
dcm_task_df[DcmTask.id.key] = dcm_task_df[DcmTask.id.key].astype(str)
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||||
|
||||
# 预处理数据方法
|
||||
def preprocess(df: pd.DataFrame):
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||||
# 更名，并仅保留需要的列
|
||||
df = df.rename(columns=DcmTaskMoreInfoMapping)
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||||
df['content'] = df['time'].fillna("") + ' ' + df['human_name'].fillna("") + df['msg_type'].fillna("")
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df = df[list(DcmTaskMoreInfoMapping.values()) + ['content',DcmTaskMoreInfo.dcm_task_id.key]]
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return df
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||||
# 填充表单数据
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||||
await DcmTaskMoreInfo.fill_more_info(dcm_task_df, column_name='moreInfoList', preprocessing=preprocess)
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||||
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||||
# 处理无待办工单更多信息状态
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||||
empty_dcm_task_df = dcm_task_df[dcm_task_df['moreInfoList'].apply(lambda x: len(x) == 0)]
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||||
empty_dcm_task_df[DcmPushStatus.dcm_task_id.key] = empty_dcm_task_df[DcmTask.id.key]
|
||||
empty_dcm_task_df[DcmPushStatus.push_task_more_info_status.key] = 1
|
||||
empty_dcm_task_df = empty_dcm_task_df[[DcmPushStatus.dcm_task_id.key, DcmPushStatus.push_task_more_info_status.key]]
|
||||
await DcmPushStatus.save_batch(empty_dcm_task_df)
|
||||
|
||||
# 过滤空数组
|
||||
full_dcm_task_df = dcm_task_df[dcm_task_df['moreInfoList'].apply(lambda x: len(x) > 0)]
|
||||
# 删除 DcmTaskMoreInfo.dcm_task_id.key 字段
|
||||
def remove_dcm_task_id(attachment_list):
|
||||
for item in attachment_list:
|
||||
if isinstance(item, dict) and DcmTaskMoreInfo.dcm_task_id.key in item:
|
||||
del item[DcmTaskMoreInfo.dcm_task_id.key]
|
||||
return attachment_list
|
||||
|
||||
# 执行替换
|
||||
full_dcm_task_df['moreInfoList'] = full_dcm_task_df['moreInfoList'].apply(remove_dcm_task_id)
|
||||
|
||||
# 处理数据映射，适应接口推送
|
||||
mapped_df = full_dcm_task_df.rename(columns={DcmTask.id.key: 'gdId'})
|
||||
# 这里把空数据都换成 None，以便存入数据库时是 null
|
||||
mapped_df.replace(models.EmptyInDF + models.EmptyDatetimeInDF, '', inplace=True)
|
||||
|
||||
echo_log(f"正在准备请求队列...")
|
||||
# 构建请求队列
|
||||
dcm_push_queue = asyncio.Queue()
|
||||
|
||||
# 向队列中填充请求对象
|
||||
for _h, row in mapped_df.iterrows():
|
||||
push_request = await oa_api_request.get_push_more_info_request(**row.to_dict())
|
||||
setattr(push_request, "dcm_task_id", row.get('gdId'))
|
||||
await dcm_push_queue.put(push_request)
|
||||
|
||||
# 并发提交推送请求
|
||||
echo_log(f"开始推送更多信息数据...")
|
||||
await requests.async_concurrency(
|
||||
dcm_push_queue, con_count=dock.CONCURRENCY_COUNT, retry=dock.MAX_RETRY_COUNT,
|
||||
after_request=after_push_more_info_request
|
||||
)
|
||||
echo_log(f"更多信息数据推送已经完成...")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
from paste.core import aio_pool
|
||||
|
||||
_runner = aio_pool.get_aio_runner()
|
||||
_runner(push_more_info(task_id=2054174091237265408))
|
||||
@@ -0,0 +1,241 @@
|
||||
"""
|
||||
待办工单推送。
|
||||
|
||||
对应文档接口：2、推送待办工单列表
|
||||
"""
|
||||
import asyncio
|
||||
import json
|
||||
from typing import Optional, Union
|
||||
|
||||
import pandas as pd
|
||||
from sqlalchemy import select, desc
|
||||
from tornado.httpclient import HTTPResponse, HTTPRequest
|
||||
|
||||
import dock
|
||||
import models
|
||||
from dock.oa import oa_api_request
|
||||
from models.dcm_push_status import DcmPushStatus
|
||||
from models.dcm_task import DcmTask
|
||||
from paste.core.logging import echo_log
|
||||
from paste.util import udict
|
||||
from paste.web import requests
|
||||
|
||||
DcmTaskMapping = {
|
||||
DcmTask.id.key: 'gdId',
|
||||
DcmTask.task_num.key: 'taskNum',
|
||||
DcmTask.other_task_num.key: 'otherTaskNum',
|
||||
DcmTask.bundle_deadline_time.key: 'bundleDeadlineTimeStr',
|
||||
DcmTask.rollback_deadline.key: 'rollbackDeadlineStr',
|
||||
DcmTask.event_src_name.key: 'eventSrcName',
|
||||
DcmTask.rec_type_name.key: 'recTypeName',
|
||||
DcmTask.event_type_name.key: 'eventTypeName',
|
||||
DcmTask.main_type_name.key: 'mainTypeName',
|
||||
DcmTask.sub_type_name.key: 'subTypeName',
|
||||
DcmTask.urgency_level.key: 'urgencyLevel',
|
||||
DcmTask.event_desc.key: 'eventDesc',
|
||||
DcmTask.address.key: 'address',
|
||||
DcmTask.processing_deadline.key: 'disposalTimeLimit',
|
||||
DcmTask.district_name.key: 'districtName',
|
||||
DcmTask.new_inst_cond_name.key: 'newInstCondName',
|
||||
DcmTask.case_closure_condition.key: 'closingConditions',
|
||||
DcmTask.reporter_name.key: 'reporterName',
|
||||
DcmTask.reporter_contact.key: 'reporterContact',
|
||||
DcmTask.reply_intime.key: 'replyIntime',
|
||||
DcmTask.first_depart_name.key: 'firstDepartName',
|
||||
DcmTask.second_depart_name.key: 'secondDepartName',
|
||||
DcmTask.bundle_warning_time.key: 'bundleWarningTimeStr',
|
||||
DcmTask.act_ard_state_name.key: 'actArdStateName',
|
||||
DcmTask.operation.key: 'operateType',
|
||||
}
|
||||
"""
|
||||
数据推送映射关系。
|
||||
"""
|
||||
|
||||
|
||||
async def after_push_order_request(response: HTTPResponse, retry_queue: asyncio.Queue[HTTPRequest]):
|
||||
"""
|
||||
工单推送请求响应后的处理程序。
|
||||
|
||||
:param response: 响应对象
|
||||
:param retry_queue: 重试队列
|
||||
"""
|
||||
body = response.body.decode()
|
||||
echo_log(body)
|
||||
body_data = json.loads(body)
|
||||
code = udict.get_by_path(body_data, 'code')
|
||||
message = udict.get_by_path(body_data, 'msg')
|
||||
if code == 200:
|
||||
dcm_task_id_list = getattr(response.request, "dcm_task_id_list", [])
|
||||
dcm_task_push_data = [
|
||||
{
|
||||
DcmPushStatus.dcm_task_id.key: dcm_task_id,
|
||||
DcmPushStatus.push_task_status.key: 1
|
||||
}
|
||||
for dcm_task_id in dcm_task_id_list
|
||||
]
|
||||
dcm_task_push_df = pd.DataFrame(dcm_task_push_data)
|
||||
await DcmPushStatus.save_batch(dcm_task_push_df)
|
||||
echo_log(f"推送企业待办成功.")
|
||||
else:
|
||||
echo_log(f"推送企业待办失败：{message}")
|
||||
|
||||
if retry_queue:
|
||||
echo_log(f"企业待办重试队列中有：{retry_queue.qsize()} 个请求在等待.")
|
||||
|
||||
|
||||
async def push_order(fetch_size: int = 50, batch_size: int = 10,
|
||||
task_id: Optional[Union[str, int, list[Union[str, int]]]] = None):
|
||||
"""
|
||||
推送待办数据及其数据。
|
||||
|
||||
:param fetch_size: 本次推送数量
|
||||
:param batch_size: 分批时，每批大小
|
||||
:param task_id: 待办任务 ID 可选
|
||||
"""
|
||||
# 根据条件获取目标任务 ID 列表（支持指定 task_id 或分页获取）
|
||||
task_query = select(
|
||||
DcmTask.id,
|
||||
DcmTask.task_num, DcmTask.other_task_num,
|
||||
DcmTask.bundle_deadline_time, DcmTask.rollback_deadline,
|
||||
DcmTask.event_src_name, DcmTask.rec_type_name,
|
||||
DcmTask.event_type_name, DcmTask.main_type_name,
|
||||
DcmTask.sub_type_name, DcmTask.urgency_level,
|
||||
DcmTask.event_desc, DcmTask.address,
|
||||
DcmTask.processing_deadline, DcmTask.district_name,
|
||||
DcmTask.new_inst_cond_name, DcmTask.case_closure_condition,
|
||||
DcmTask.reporter_name, DcmTask.reporter_contact,
|
||||
DcmTask.reply_intime, DcmTask.first_depart_name,
|
||||
DcmTask.second_depart_name, DcmTask.bundle_warning_time,
|
||||
DcmTask.act_ard_state_name, DcmTask.operation
|
||||
).order_by(
|
||||
desc(DcmTask.act_id)
|
||||
)
|
||||
if task_id:
|
||||
if isinstance(task_id, list):
|
||||
task_query = task_query.where(DcmTask.id.in_(task_id))
|
||||
echo_log(f"本次推送待办列表：{task_id} 的数据...")
|
||||
else:
|
||||
task_query = task_query.where(DcmTask.id == task_id)
|
||||
echo_log(f"本次推送待办：{task_id} 的数据...")
|
||||
else:
|
||||
task_query = task_query.limit(fetch_size)
|
||||
echo_log(f"本次推送前 {fetch_size} 条待办数据...")
|
||||
|
||||
# if apps.get_active_env() == 'prod':
|
||||
# # 生产环境只推送 DcmTaskProcessInfo.action_time > 2026-05-18 00:00:00 的待办工单
|
||||
# # 构建子查询：查找满足条件的 DcmTaskProcessInfo
|
||||
# subquery = select(DcmTaskProcessInfo.dcm_task_id).where(
|
||||
# DcmTaskProcessInfo.dcm_task_id == DcmTask.id,
|
||||
# DcmTaskProcessInfo.action_time > '2026-05-18 00:00:00'
|
||||
# ).group_by(
|
||||
# DcmTaskProcessInfo.dcm_task_id
|
||||
# ).order_by(
|
||||
# desc(DcmTaskProcessInfo.action_time)
|
||||
# )
|
||||
# task_query = task_query.where(exists(subquery))
|
||||
|
||||
dcm_task_df = await DcmTask.query_as_df(task_query)
|
||||
# 格式化三个时间字段为 yyyy-MM-dd HH:mm:ss
|
||||
dcm_task_df[DcmTask.bundle_deadline_time.key] = (
|
||||
pd.to_datetime(
|
||||
dcm_task_df[DcmTask.bundle_deadline_time.key], unit='ms', errors='coerce'
|
||||
).dt.strftime('%Y-%m-%d %H:%M:%S')
|
||||
)
|
||||
dcm_task_df[DcmTask.rollback_deadline.key] = (
|
||||
pd.to_datetime(
|
||||
dcm_task_df[DcmTask.rollback_deadline.key], unit='ms', errors='coerce'
|
||||
).dt.strftime('%Y-%m-%d %H:%M:%S'))
|
||||
dcm_task_df[DcmTask.bundle_warning_time.key] = (
|
||||
pd.to_datetime(
|
||||
dcm_task_df[DcmTask.bundle_warning_time.key], unit='ms', errors='coerce'
|
||||
).dt.strftime('%Y-%m-%d %H:%M:%S'))
|
||||
# 格式化为字符串
|
||||
dcm_task_df[DcmTask.id.key] = dcm_task_df[DcmTask.id.key].astype(str)
|
||||
# 代码转义
|
||||
reply_intime_map = {
|
||||
'0': '无需回复',
|
||||
'1': '待回复',
|
||||
'2': '已回复',
|
||||
'3': '超时未回复',
|
||||
'4': '无需回复已恢复',
|
||||
}
|
||||
dcm_task_df[DcmTask.reply_intime.key] = dcm_task_df[DcmTask.reply_intime.key].astype(str).map(
|
||||
lambda x: reply_intime_map.get(x, x)
|
||||
)
|
||||
urgency_level_map = {
|
||||
'0': '正常',
|
||||
'1': '紧急',
|
||||
}
|
||||
dcm_task_df[DcmTask.urgency_level.key] = dcm_task_df[DcmTask.urgency_level.key].astype(str).map(
|
||||
lambda x: urgency_level_map.get(x, x)
|
||||
)
|
||||
|
||||
dcm_task_df[DcmTask.operation.key] = dcm_task_df[DcmTask.operation.key].str.split(',')
|
||||
|
||||
# 处理数据映射，适应接口推送
|
||||
mapped_df = dcm_task_df.rename(columns=DcmTaskMapping)
|
||||
# 这里把空数据都换成 None，以便存入数据库时是 null
|
||||
mapped_df.replace(models.EmptyInDF + models.EmptyDatetimeInDF, '', inplace=True)
|
||||
|
||||
echo_log(f"正在准备请求队列...")
|
||||
# 构建请求队列
|
||||
dcm_push_queue = asyncio.Queue()
|
||||
|
||||
# 向队列中填充请求对象
|
||||
for start in range(0, len(mapped_df), batch_size):
|
||||
batch_df: pd.DataFrame = mapped_df.iloc[start:start + batch_size]
|
||||
push_list = batch_df.to_dict('records')
|
||||
push_request = await oa_api_request.get_push_order_request(push_list)
|
||||
setattr(push_request, "dcm_task_id_list", batch_df['gdId'].unique().tolist())
|
||||
await dcm_push_queue.put(push_request)
|
||||
|
||||
# 并发提交推送请求
|
||||
echo_log(f"开始推送待办数据...")
|
||||
await requests.async_concurrency(
|
||||
dcm_push_queue, con_count=dock.CONCURRENCY_COUNT, retry=dock.MAX_RETRY_COUNT,
|
||||
after_request=after_push_order_request
|
||||
)
|
||||
echo_log(f"待办数据推送已经完成...")
|
||||
|
||||
|
||||
async def push_full_order(fetch_size: int = 50, batch_size: int = 10,
|
||||
task_id: Optional[Union[str, int, list[Union[str, int]]]] = None):
|
||||
from dock.oa_dcm import oa_push_order_detail, oa_push_process_info, oa_push_attachment, \
|
||||
oa_push_more_info, oa_push_extend_info, oa_upload
|
||||
|
||||
await push_order(fetch_size, batch_size, task_id)
|
||||
await oa_push_order_detail.push_order_detail(fetch_size, task_id)
|
||||
await oa_push_process_info.push_process_info(fetch_size, task_id)
|
||||
await oa_upload.upload_with_attachment(fetch_size, task_id)
|
||||
await oa_push_attachment.push_attachment(fetch_size, task_id)
|
||||
await oa_push_more_info.push_more_info(fetch_size, task_id)
|
||||
await oa_push_extend_info.push_extend_info(fetch_size, task_id)
|
||||
|
||||
|
||||
async def push_sign_order():
|
||||
"""
|
||||
推送并签收工单。
|
||||
"""
|
||||
from dock.oa_dcm import oa_push_order_detail, oa_push_process_info, oa_push_attachment, \
|
||||
oa_push_more_info, oa_push_extend_info, oa_upload, oa_sign_task
|
||||
|
||||
# TODO: 查询得到要推送的工单ID列表
|
||||
task_id_list = []
|
||||
|
||||
if task_id_list:
|
||||
await push_order(task_id=task_id_list)
|
||||
await oa_push_order_detail.push_order_detail(task_id=task_id_list)
|
||||
await oa_push_process_info.push_process_info(task_id=task_id_list)
|
||||
await oa_upload.upload_with_attachment(task_id=task_id_list)
|
||||
await oa_push_attachment.push_attachment(task_id=task_id_list)
|
||||
await oa_push_more_info.push_more_info(task_id=task_id_list)
|
||||
await oa_push_extend_info.push_extend_info(task_id=task_id_list)
|
||||
# 推送结束后，签收工单
|
||||
await oa_sign_task.sign_task(task_id=task_id_list)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
from paste.core import aio_pool
|
||||
|
||||
_runner = aio_pool.get_aio_runner()
|
||||
_runner(push_order(task_id=2054174091254042627))
|
||||
@@ -0,0 +1,165 @@
|
||||
"""
|
||||
待办工单明细推送。
|
||||
|
||||
对应文档接口：5、推送工单详情
|
||||
"""
|
||||
import asyncio
|
||||
import json
|
||||
from typing import Optional, Union
|
||||
|
||||
import pandas as pd
|
||||
from sqlalchemy import select, desc
|
||||
from tornado.httpclient import HTTPResponse, HTTPRequest
|
||||
|
||||
import dock
|
||||
import models
|
||||
from dock.oa import oa_api_request
|
||||
from models.dcm_push_status import DcmPushStatus
|
||||
from models.dcm_task import DcmTask
|
||||
from models.dcm_task_form_datum import DcmTaskFormDatum
|
||||
from paste.core.logging import echo_log
|
||||
from paste.util import udict
|
||||
from paste.web import requests
|
||||
|
||||
DcmTaskMapping = {
|
||||
DcmTask.id.key: 'gdId',
|
||||
DcmTask.part_code.key: 'partCode',
|
||||
DcmTaskFormDatum.func_limit_char.key: 'funcLimitChar',
|
||||
DcmTask.reporter_name.key: 'reporterName',
|
||||
DcmTaskFormDatum.media_upload_total_num.key: 'mediaUploadTotalNum',
|
||||
DcmTask.return_visit_flag.key:'returnVisitFlag',
|
||||
DcmTask.func_forbid_reporter_info_flag.key:'funcForbidReporterInfoFlag',
|
||||
DcmTaskFormDatum.tell_num.key:'contactNumberDd',
|
||||
DcmTask.reporter_contact.key: 'reportNumberDd',
|
||||
DcmTaskFormDatum.deal_person_org.key: 'dealPersonOrg',
|
||||
DcmTaskFormDatum.undertake_user_name.key: 'undertakeUserName',
|
||||
}
|
||||
"""
|
||||
数据推送映射关系。
|
||||
"""
|
||||
|
||||
|
||||
async def after_push_order_detail_request(response: HTTPResponse, retry_queue: asyncio.Queue[HTTPRequest]):
|
||||
"""
|
||||
工单推送请求响应后的处理程序。
|
||||
|
||||
:param response: 响应对象
|
||||
:param retry_queue: 重试队列
|
||||
"""
|
||||
body = response.body.decode()
|
||||
echo_log(body)
|
||||
body_data = json.loads(body)
|
||||
code = udict.get_by_path(body_data, 'code')
|
||||
message = udict.get_by_path(body_data, 'msg')
|
||||
if code==200:
|
||||
dcm_task_id = getattr(response.request, "dcm_task_id")
|
||||
await DcmPushStatus.set_push_task_detail_status(dcm_task_id)
|
||||
echo_log(f"推送工单详情成功.")
|
||||
else:
|
||||
echo_log(f"推送工单详情失败：{message}")
|
||||
|
||||
if retry_queue:
|
||||
echo_log(f"工单详情重试队列中有：{retry_queue.qsize()} 个请求在等待.")
|
||||
|
||||
|
||||
async def push_order_detail(fetch_size: int = 50,
|
||||
task_id: Optional[Union[str, int, list[Union[str, int]]]] = None):
|
||||
"""
|
||||
推送待办数据及其数据。
|
||||
|
||||
:param fetch_size: 本次推送数量
|
||||
:param task_id: 待办任务 ID 可选
|
||||
"""
|
||||
# 根据条件获取目标任务 ID 列表（支持指定 task_id 或分页获取）
|
||||
task_query = select(DcmTask.id).order_by(desc(DcmTask.act_id))
|
||||
if task_id:
|
||||
if isinstance(task_id, list):
|
||||
task_query = task_query.where(DcmTask.id.in_(task_id))
|
||||
echo_log(f"本次推送待办列表：{task_id} 的详细数据...")
|
||||
else:
|
||||
task_query = task_query.where(DcmTask.id == task_id)
|
||||
echo_log(f"本次推送待办：{task_id} 的详细数据...")
|
||||
else:
|
||||
task_query = task_query.limit(fetch_size)
|
||||
echo_log(f"本次推送前 {fetch_size} 条待办的详细数据...")
|
||||
task_id_list = (await DcmTask.orm_execute_scalars(task_query)).all()
|
||||
task_id_list = [f"{id}" for id in task_id_list]
|
||||
|
||||
# 查询属于这些任务的所有详细数据
|
||||
datum_query = select(
|
||||
DcmTask.id, DcmTask.part_code, DcmTask.reporter_name, DcmTask.reporter_contact,
|
||||
DcmTask.return_visit_flag, DcmTask.func_forbid_reporter_info_flag,
|
||||
DcmTaskFormDatum.media_upload_total_num, DcmTaskFormDatum.func_limit_char,
|
||||
DcmTaskFormDatum.tell_num, DcmTaskFormDatum.undertake_user_name,
|
||||
DcmTaskFormDatum.deal_person_org
|
||||
).join(
|
||||
DcmTaskFormDatum, DcmTask.id==DcmTaskFormDatum.dcm_task_id
|
||||
).where(
|
||||
DcmTask.id.in_(task_id_list)
|
||||
)
|
||||
|
||||
dcm_task_df = await DcmTask.query_as_df(datum_query)
|
||||
# 格式化为字符串
|
||||
dcm_task_df[DcmTask.id.key] = dcm_task_df[DcmTask.id.key].astype(str)
|
||||
dcm_task_df[DcmTaskFormDatum.media_upload_total_num.key] = dcm_task_df[DcmTaskFormDatum.media_upload_total_num.key].fillna(0).astype(int)
|
||||
# 代码转义
|
||||
return_visit_flag_map = {
|
||||
'0': '无需回访',
|
||||
'1': '待回访',
|
||||
'2': '已回访',
|
||||
}
|
||||
dcm_task_df[DcmTask.return_visit_flag.key] = dcm_task_df[DcmTask.return_visit_flag.key].astype(str).map(
|
||||
lambda x: return_visit_flag_map.get(x, x)
|
||||
)
|
||||
func_forbid_reporter_info_flag_map = {
|
||||
'0': '否',
|
||||
'1': '是',
|
||||
}
|
||||
dcm_task_df[DcmTask.func_forbid_reporter_info_flag.key] = dcm_task_df[DcmTask.func_forbid_reporter_info_flag.key].astype(str).map(
|
||||
lambda x: func_forbid_reporter_info_flag_map.get(x, x)
|
||||
)
|
||||
|
||||
# 未爬取的字段暂时填空值
|
||||
dcm_task_df['violationTaskNoDd'] = ''
|
||||
dcm_task_df['telReply'] = ''
|
||||
|
||||
# 处理无待办工单详情状态
|
||||
empty_task_ids = set(task_id_list) - set(dcm_task_df[DcmTask.id.key].unique().tolist())
|
||||
empty_task_data = [
|
||||
{
|
||||
DcmPushStatus.dcm_task_id.key: dcm_task_id,
|
||||
DcmPushStatus.push_task_status.key: 1
|
||||
}
|
||||
for dcm_task_id in list(empty_task_ids)
|
||||
]
|
||||
empty_task_df = pd.DataFrame(empty_task_data)
|
||||
await DcmPushStatus.save_batch(empty_task_df)
|
||||
|
||||
# 处理数据映射，适应接口推送
|
||||
mapped_df = dcm_task_df.rename(columns=DcmTaskMapping)
|
||||
# 这里把空数据都换成 None，以便存入数据库时是 null
|
||||
mapped_df.replace(models.EmptyInDF + models.EmptyDatetimeInDF, '', inplace=True)
|
||||
|
||||
echo_log(f"正在准备请求队列...")
|
||||
# 构建请求队列
|
||||
dcm_push_queue = asyncio.Queue()
|
||||
|
||||
# 向队列中填充请求对象
|
||||
for _h, row in mapped_df.iterrows():
|
||||
push_request = await oa_api_request.get_push_order_detail_request(**row.to_dict())
|
||||
setattr(push_request, "dcm_task_id", row.get('gdId'))
|
||||
await dcm_push_queue.put(push_request)
|
||||
|
||||
# 并发提交推送请求
|
||||
echo_log(f"开始推送工单详情数据...")
|
||||
await requests.async_concurrency(
|
||||
dcm_push_queue, con_count=dock.CONCURRENCY_COUNT, retry=dock.MAX_RETRY_COUNT,
|
||||
after_request=after_push_order_detail_request
|
||||
)
|
||||
echo_log(f"工单详情推送已经完成...")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
from paste.core import aio_pool
|
||||
_runner = aio_pool.get_aio_runner()
|
||||
_runner(push_order_detail(task_id=2054174091254042627))
|
||||
@@ -0,0 +1,164 @@
|
||||
"""
|
||||
推送办理经过。
|
||||
|
||||
对应文档接口：6、推送办理经过
|
||||
"""
|
||||
import asyncio
|
||||
import json
|
||||
from typing import Optional, Union
|
||||
|
||||
import pandas as pd
|
||||
from sqlalchemy import select, desc
|
||||
from tornado.httpclient import HTTPResponse, HTTPRequest
|
||||
|
||||
import dock
|
||||
import models
|
||||
from dock.oa import oa_api_request
|
||||
from models.dcm_push_status import DcmPushStatus
|
||||
from models.dcm_task import DcmTask
|
||||
from models.dcm_task_process_info import DcmTaskProcessInfo
|
||||
from paste.core.logging import echo_log
|
||||
from paste.util import udict
|
||||
from paste.web import requests
|
||||
|
||||
DcmTaskProcessInfoMapping = {
|
||||
DcmTaskProcessInfo.id.key: 'id',
|
||||
DcmTaskProcessInfo.action_time.key: 'actionTime',
|
||||
DcmTaskProcessInfo.act_def_name.key: 'actDefName',
|
||||
DcmTaskProcessInfo.human_name.key: 'humanName',
|
||||
DcmTaskProcessInfo.unit_name.key: 'unitName',
|
||||
DcmTaskProcessInfo.action_name.key: 'actionName',
|
||||
DcmTaskProcessInfo.next_act_def_name.key: 'nextActDefName',
|
||||
DcmTaskProcessInfo.detail.key: 'detail',
|
||||
}
|
||||
|
||||
|
||||
async def after_push_process_info_request(response: HTTPResponse, retry_queue: asyncio.Queue[HTTPRequest]):
|
||||
"""
|
||||
工单推送请求响应后的处理程序。
|
||||
|
||||
:param response: 响应对象
|
||||
:param retry_queue: 重试队列
|
||||
"""
|
||||
body = response.body.decode()
|
||||
echo_log(body)
|
||||
body_data = json.loads(body)
|
||||
code = udict.get_by_path(body_data, 'code')
|
||||
message = udict.get_by_path(body_data, 'msg')
|
||||
if code==200:
|
||||
dcm_task_id = getattr(response.request, "dcm_task_id")
|
||||
await DcmPushStatus.set_push_task_process_info_status(dcm_task_id)
|
||||
echo_log(f"推送企业待办过程成功.")
|
||||
else:
|
||||
echo_log(f"推送企业待办过程失败：{message}")
|
||||
|
||||
if retry_queue:
|
||||
echo_log(f"企业待办过程重试队列中有：{retry_queue.qsize()} 个请求在等待.")
|
||||
|
||||
|
||||
async def push_process_info(fetch_size: int = 50,
|
||||
task_id: Optional[Union[str, int, list[Union[str, int]]]] = None):
|
||||
"""
|
||||
推送待办附件数据及其数据。
|
||||
|
||||
:param fetch_size: 本次推送数量
|
||||
:param task_id: 待办任务 ID 可选
|
||||
"""
|
||||
# 根据条件获取目标任务 ID 列表（支持指定 task_id 或分页获取）
|
||||
task_query = select(DcmTask.id).order_by(desc(DcmTask.act_id))
|
||||
if task_id:
|
||||
if isinstance(task_id, list):
|
||||
task_query = task_query.where(DcmTask.id.in_(task_id))
|
||||
echo_log(f"本次推送待办列表：{task_id} 的过程数据...")
|
||||
else:
|
||||
task_query = task_query.where(DcmTask.id == task_id)
|
||||
echo_log(f"本次推送待办：{task_id} 的过程数据...")
|
||||
else:
|
||||
task_query = task_query.limit(fetch_size)
|
||||
echo_log(f"本次推送前 {fetch_size} 条待办过程数据...")
|
||||
dcm_task_df = await DcmTask.query_as_df(task_query)
|
||||
|
||||
# 格式化为字符串
|
||||
dcm_task_df[DcmTask.id.key] = dcm_task_df[DcmTask.id.key].astype(str)
|
||||
dcm_task_ids = dcm_task_df[DcmTask.id.key].unique().tolist()
|
||||
dcm_task_check_info = {f'{tid}': '' for tid in dcm_task_ids}
|
||||
|
||||
# 预处理数据方法
|
||||
def preprocess(df: pd.DataFrame):
|
||||
# 格式化时间字段为 yyyy-MM-dd HH:mm:ss
|
||||
df[DcmTaskProcessInfo.action_time.key] = (
|
||||
pd.to_datetime(
|
||||
df[DcmTaskProcessInfo.action_time.key], unit='ms', errors='coerce'
|
||||
).dt.strftime('%Y-%m-%d %H:%M:%S')
|
||||
)
|
||||
|
||||
# 设置 check_info
|
||||
for tid in dcm_task_ids:
|
||||
filtered = df[df[DcmTaskProcessInfo.dcm_task_id.key] == tid].copy()
|
||||
if not filtered.empty:
|
||||
min_row = filtered.loc[filtered[DcmTaskProcessInfo.item_id.key].idxmin()].iloc[0]
|
||||
dcm_task_check_info[tid] = (
|
||||
f"{min_row[DcmTaskProcessInfo.action_time.key]}"
|
||||
f"{min_row[DcmTaskProcessInfo.human_name.key]}"
|
||||
f"在{min_row[DcmTaskProcessInfo.act_def_name.key]}阶段"
|
||||
f"{min_row[DcmTaskProcessInfo.action_name.key]}"
|
||||
)
|
||||
|
||||
# 更名，并仅保留需要的列
|
||||
df = df.rename(columns=DcmTaskProcessInfoMapping)
|
||||
df = df[list(DcmTaskProcessInfoMapping.values()) + [DcmTaskProcessInfo.dcm_task_id.key]]
|
||||
return df
|
||||
|
||||
# 填充处理过程
|
||||
await DcmTaskProcessInfo.fill_process_info(dcm_task_df, column_name='handlingProcessList', preprocessing=preprocess)
|
||||
|
||||
# 处理无待办工单处理过程状态
|
||||
empty_dcm_task_df = dcm_task_df[dcm_task_df['handlingProcessList'].apply(lambda x: len(x) == 0)]
|
||||
empty_dcm_task_df[DcmPushStatus.dcm_task_id.key] = empty_dcm_task_df[DcmTask.id.key]
|
||||
empty_dcm_task_df[DcmPushStatus.push_task_process_info_status.key] = 1
|
||||
empty_dcm_task_df = empty_dcm_task_df[[DcmPushStatus.dcm_task_id.key, DcmPushStatus.push_task_process_info_status.key]]
|
||||
await DcmPushStatus.save_batch(empty_dcm_task_df)
|
||||
|
||||
# 过滤空数组
|
||||
full_dcm_task_df = dcm_task_df[dcm_task_df['handlingProcessList'].apply(lambda x: len(x) > 0)]
|
||||
# 删除 DcmTaskAttachment.dcm_task_id.key 字段
|
||||
def remove_dcm_task_id(attachment_list):
|
||||
for item in attachment_list:
|
||||
if isinstance(item, dict) and DcmTaskProcessInfo.dcm_task_id.key in item:
|
||||
del item[DcmTaskProcessInfo.dcm_task_id.key]
|
||||
return attachment_list
|
||||
# 执行替换
|
||||
full_dcm_task_df['handlingProcessList'] = full_dcm_task_df['handlingProcessList'].apply(remove_dcm_task_id)
|
||||
# 增加 checkContent 字段，来自办理流程数据合并
|
||||
full_dcm_task_df['checkContent'] = full_dcm_task_df[DcmTask.id.key].apply(
|
||||
lambda x: dcm_task_check_info.get(x, '')
|
||||
)
|
||||
|
||||
# 处理数据映射，适应接口推送
|
||||
mapped_df = full_dcm_task_df.rename(columns={DcmTask.id.key: 'gdId'})
|
||||
# 这里把空数据都换成 None，以便存入数据库时是 null
|
||||
mapped_df.replace(models.EmptyInDF + models.EmptyDatetimeInDF, '', inplace=True)
|
||||
|
||||
echo_log(f"正在准备请求队列...")
|
||||
# 构建请求队列
|
||||
dcm_push_queue = asyncio.Queue()
|
||||
|
||||
# 向队列中填充请求对象
|
||||
for _h, row in mapped_df.iterrows():
|
||||
push_request = await oa_api_request.get_push_process_info_request(**row.to_dict())
|
||||
setattr(push_request, "dcm_task_id", row.get('gdId'))
|
||||
await dcm_push_queue.put(push_request)
|
||||
|
||||
# 并发提交推送请求
|
||||
echo_log(f"开始推送待办过程数据...")
|
||||
await requests.async_concurrency(
|
||||
dcm_push_queue, con_count=dock.CONCURRENCY_COUNT, retry=dock.MAX_RETRY_COUNT,
|
||||
after_request=after_push_process_info_request
|
||||
)
|
||||
echo_log(f"待办过程数据推送已经完成...")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
from paste.core import aio_pool
|
||||
_runner = aio_pool.get_aio_runner()
|
||||
_runner(push_process_info(task_id=2054174091237265408))
|
||||
@@ -0,0 +1,98 @@
|
||||
"""
|
||||
向 OA 平台上报数据已经完整推送。
|
||||
|
||||
对应文档接口：11、签收
|
||||
"""
|
||||
import asyncio
|
||||
import json
|
||||
from typing import Optional, Union
|
||||
|
||||
from sqlalchemy import select, desc
|
||||
from tornado.httpclient import HTTPResponse, HTTPRequest
|
||||
|
||||
import dock
|
||||
from dock.oa import oa_api_request
|
||||
from models.dcm_push_status import DcmPushStatus
|
||||
from models.dcm_task import DcmTask
|
||||
from paste.core.logging import echo_log
|
||||
from paste.util import udict
|
||||
from paste.web import requests
|
||||
|
||||
|
||||
async def after_sign_task_request(response: HTTPResponse, retry_queue: asyncio.Queue[HTTPRequest]):
|
||||
"""
|
||||
签收工单请求响应后的处理程序。
|
||||
|
||||
:param response: 响应对象
|
||||
:param retry_queue: 重试队列
|
||||
"""
|
||||
body = response.body.decode()
|
||||
echo_log(body)
|
||||
body_data = json.loads(body)
|
||||
code = udict.get_by_path(body_data, 'code')
|
||||
message = udict.get_by_path(body_data, 'msg')
|
||||
if code == 200:
|
||||
echo_log(f"签收工单成功.")
|
||||
else:
|
||||
echo_log(f"签收工单失败：{message}")
|
||||
|
||||
if retry_queue:
|
||||
echo_log(f"签收工单重试队列中有：{retry_queue.qsize()} 个请求在等待.")
|
||||
|
||||
|
||||
async def sign_task(fetch_size: int = 50,
|
||||
task_id: Optional[Union[str, int, list[Union[str, int]]]] = None):
|
||||
"""
|
||||
签收指定数量的工单任务
|
||||
|
||||
:param fetch_size: 本次签收的任务数量
|
||||
:param task_id: 待办任务 ID 可选
|
||||
"""
|
||||
# 根据条件获取目标任务 ID 列表（支持指定 task_id 或分页获取）
|
||||
task_query = select(DcmTask.id).join(
|
||||
DcmPushStatus, DcmPushStatus.dcm_task_id == DcmTask.id
|
||||
).where(
|
||||
DcmPushStatus.push_task_status == 1,
|
||||
DcmPushStatus.push_task_detail_status == 1,
|
||||
DcmPushStatus.push_task_attachment_status == 1,
|
||||
DcmPushStatus.push_task_extend_info_status == 1,
|
||||
DcmPushStatus.push_task_file_upload_status == 1,
|
||||
DcmPushStatus.push_task_more_info_status == 1,
|
||||
DcmPushStatus.push_task_process_info_status == 1,
|
||||
).order_by(
|
||||
desc(DcmTask.act_id)
|
||||
)
|
||||
if task_id:
|
||||
if isinstance(task_id, list):
|
||||
task_query = task_query.where(DcmTask.id.in_(task_id))
|
||||
echo_log(f"本次签收待办列表：{task_id} 的工单...")
|
||||
else:
|
||||
task_query = task_query.where(DcmTask.id == task_id)
|
||||
echo_log(f"本次签收待办：{task_id} 的工单...")
|
||||
else:
|
||||
task_query = task_query.limit(fetch_size)
|
||||
echo_log(f"本次签收前 {fetch_size} 条待办工单...")
|
||||
|
||||
dcm_task_df = await DcmTask.query_as_df(task_query)
|
||||
# 格式化为字符串
|
||||
dcm_task_df[DcmTask.id.key] = dcm_task_df[DcmTask.id.key].astype(str)
|
||||
|
||||
echo_log(f"正在准备请求队列...")
|
||||
# 构建请求队列
|
||||
sign_request_queue = asyncio.Queue()
|
||||
task_id_list = dcm_task_df[DcmTask.id.key].unique().tolist()
|
||||
for task_id in task_id_list:
|
||||
request = await oa_api_request.get_sign_task_request(task_id)
|
||||
await sign_request_queue.put(request)
|
||||
echo_log(f"开始签收工单...")
|
||||
await requests.async_concurrency(
|
||||
sign_request_queue, con_count=dock.CONCURRENCY_COUNT, retry=dock.MAX_RETRY_COUNT,
|
||||
after_request=after_sign_task_request
|
||||
)
|
||||
echo_log(f"签收工单完成...")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
from paste.core import aio_pool
|
||||
_runner = aio_pool.get_aio_runner()
|
||||
_runner(sign_task(task_id=2054174091228876801))
|
||||
@@ -0,0 +1,88 @@
|
||||
"""
|
||||
操作数字城管的工单延期接口后，向OA推送更新后的工单时间信息
|
||||
|
||||
对应文档接口：12、更新流程延期信息
|
||||
"""
|
||||
import asyncio
|
||||
import json
|
||||
from datetime import datetime
|
||||
|
||||
from tornado.httpclient import HTTPResponse, HTTPRequest
|
||||
|
||||
import dock
|
||||
from dock.dcm import dcm_scrape
|
||||
from dock.oa import oa_api, oa_api_request
|
||||
from models.dcm_task import DcmTask
|
||||
from paste.core.logging import echo_log
|
||||
from paste.util import udict
|
||||
from paste.web import requests
|
||||
|
||||
|
||||
async def get_update_process_delay_request(data: dict):
|
||||
api_url = '/externalWorkOrder/digitalCM/updateProcessDelayInfo'
|
||||
request_body = data
|
||||
# 构造 API 请求
|
||||
return await oa_api.new_api_request(api_url, request_body)
|
||||
|
||||
|
||||
async def after_update_process_delay_request(response: HTTPResponse, retry_queue: asyncio.Queue[HTTPRequest]):
|
||||
"""
|
||||
更新流程延期请求响应后的处理程序。
|
||||
|
||||
:param response: 响应对象
|
||||
:param retry_queue: 重试队列
|
||||
"""
|
||||
body = response.body.decode()
|
||||
echo_log(body)
|
||||
body_data = json.loads(body)
|
||||
code = udict.get_by_path(body_data, 'code')
|
||||
message = udict.get_by_path(body_data, 'msg')
|
||||
if code == 200:
|
||||
echo_log(f"更新流程延期成功.")
|
||||
else:
|
||||
echo_log(f"更新流程延期失败：{message}")
|
||||
|
||||
if retry_queue:
|
||||
echo_log(f"更新流程延期重试队列中有：{retry_queue.qsize()} 个请求在等待.")
|
||||
|
||||
|
||||
async def update_process_delay(task_id: int):
|
||||
"""
|
||||
流程延期更新之后，推送最新的时间信息
|
||||
|
||||
:param task_id: 对应的工单ID
|
||||
"""
|
||||
|
||||
echo_log(f"本次更新{task_id}的最新时间信息...")
|
||||
dcm_task = await DcmTask.async_find_by_id(task_id)
|
||||
echo_log(f"开始更新流程延期...")
|
||||
await dcm_scrape.fetch_single_dcm_task(dcm_task)
|
||||
# 重新获取更新后的任务对象
|
||||
dcm_task: DcmTask = await DcmTask.async_find_by_id(task_id)
|
||||
if dcm_task is not None:
|
||||
bundle_deadline_time_str = datetime.fromtimestamp(
|
||||
dcm_task.bundle_deadline_time // 1000
|
||||
).strftime("%Y-%m-%d %H:%M:%S") if dcm_task.bundle_deadline_time else ''
|
||||
|
||||
rollback_deadline_str = datetime.fromtimestamp(
|
||||
dcm_task.rollback_deadline // 1000
|
||||
).strftime("%Y-%m-%d %H:%M:%S") if dcm_task.rollback_deadline else ''
|
||||
|
||||
request = await oa_api_request.get_update_process_delay_request(
|
||||
str(task_id), bundle_deadline_time_str, rollback_deadline_str
|
||||
)
|
||||
queue = asyncio.Queue()
|
||||
await queue.put(request)
|
||||
await requests.async_concurrency(
|
||||
queue, con_count=dock.CONCURRENCY_COUNT, retry=dock.MAX_RETRY_COUNT,
|
||||
after_request=after_update_process_delay_request
|
||||
)
|
||||
|
||||
echo_log(f"更新流程延期完成...")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
from paste.core import aio_pool
|
||||
|
||||
_runner = aio_pool.get_aio_runner()
|
||||
_runner(update_process_delay(task_id=2054174091228876801))
|
||||
@@ -0,0 +1,204 @@
|
||||
"""
|
||||
待办工单附件文件上传。
|
||||
|
||||
对应文档接口：3、文件上传接口
|
||||
"""
|
||||
import asyncio
|
||||
import hashlib
|
||||
import io
|
||||
import json
|
||||
from typing import Union, Optional
|
||||
from urllib.parse import urlparse
|
||||
|
||||
import pandas as pd
|
||||
from sqlalchemy import select, desc, exists
|
||||
from tornado.httpclient import HTTPResponse, HTTPRequest
|
||||
|
||||
import apps
|
||||
import dock
|
||||
from dock.oa import oa_api_request
|
||||
from models.dcm_push_status import DcmPushStatus
|
||||
from models.dcm_task import DcmTask
|
||||
from models.dcm_task_attachment import DcmTaskAttachment
|
||||
from models.dcm_task_file_upload import DcmTaskFileUpload
|
||||
from paste.core.logging import echo_log
|
||||
from paste.util import udict
|
||||
from paste.web import requests
|
||||
|
||||
file_url_column_name = '_file_url'
|
||||
"""
|
||||
文件路径列名。
|
||||
"""
|
||||
|
||||
|
||||
async def done_attachment_download(response_list: list[HTTPResponse]):
|
||||
"""
|
||||
下载全部完成后处理程序。
|
||||
|
||||
:param response_list: 响应列表
|
||||
:return:
|
||||
"""
|
||||
echo_log(f"文件下载全部完成...")
|
||||
|
||||
|
||||
async def after_attachment_upload(response: HTTPResponse, retry_queue: asyncio.Queue[HTTPRequest]):
|
||||
"""
|
||||
附件上传请求后处理程序。
|
||||
|
||||
:param response: 响应对象
|
||||
:param retry_queue: 重试队列
|
||||
"""
|
||||
task_file_upload_id = getattr(response.request, 'dcm_task_file_upload_id')
|
||||
dcm_task_id = getattr(response.request, 'dcm_task_id')
|
||||
|
||||
body = response.body.decode()
|
||||
echo_log(body)
|
||||
body_data = json.loads(body)
|
||||
nas = udict.get_by_path(body_data, 'n_a_s')
|
||||
if nas:
|
||||
oa_media_id = body_data.get('atts', [])[0].get('fileUrl')
|
||||
file_upload: DcmTaskFileUpload = await DcmTaskFileUpload.async_find_by_id(task_file_upload_id)
|
||||
file_upload.oa_media_id = oa_media_id
|
||||
file_upload.status = 1
|
||||
await file_upload.async_save()
|
||||
|
||||
dcm_task_id = getattr(response.request, "dcm_task_id")
|
||||
await DcmPushStatus.set_push_task_file_upload_status(dcm_task_id)
|
||||
echo_log(f"待办：{dcm_task_id} 的附件上传成功.")
|
||||
else:
|
||||
echo_log(f"待办：{dcm_task_id} 的附件上传失败.")
|
||||
|
||||
|
||||
async def after_attachment_download(response: HTTPResponse, retry_queue: asyncio.Queue[HTTPRequest]):
|
||||
"""
|
||||
附件下载请求后处理程序。
|
||||
|
||||
:param response: 请求对象
|
||||
:param retry_queue: 重试队列
|
||||
:return:
|
||||
"""
|
||||
dcm_task_id = getattr(response.request, 'dcm_task_id')
|
||||
dcm_task_attachment_id = getattr(response.request, 'dcm_task_attachment_id')
|
||||
dcm_media_id = getattr(response.request, 'dcm_media_id')
|
||||
# 计算文件哈希
|
||||
file_content = response.body
|
||||
file_hash = hashlib.md5(file_content).hexdigest()
|
||||
|
||||
echo_log(f"待办：{dcm_task_id} 的附件：{dcm_task_attachment_id} 已经下载完成，附件 HASH 值：{file_hash}.")
|
||||
echo_log(f"附件下载重试队列中有：{retry_queue.qsize()} 项在等待.")
|
||||
|
||||
# 保存文件上传记录数据
|
||||
file_upload_data = {
|
||||
DcmTaskFileUpload.dcm_task_id.key: dcm_task_id,
|
||||
DcmTaskFileUpload.dcm_task_attachment_id.key: dcm_task_attachment_id,
|
||||
DcmTaskFileUpload.dcm_media_id.key: dcm_media_id,
|
||||
DcmTaskFileUpload.file_hash.key: file_hash,
|
||||
}
|
||||
file_upload = await DcmTaskFileUpload.is_exist(dcm_task_id, dcm_task_attachment_id)
|
||||
if file_upload:
|
||||
file_upload.copy_from_dict(file_upload_data)
|
||||
else:
|
||||
file_upload = DcmTaskFileUpload(**file_upload_data)
|
||||
await file_upload.async_save()
|
||||
|
||||
file_obj = io.BytesIO(response.body)
|
||||
file_name = urlparse(response.request.url).path.split('/')[-1]
|
||||
upload_request = await oa_api_request.get_upload_request(file_obj, file_name=file_name)
|
||||
setattr(upload_request, 'dcm_task_file_upload_id', file_upload.id)
|
||||
setattr(upload_request, "dcm_task_id", dcm_task_id)
|
||||
upload_queue = asyncio.Queue()
|
||||
await upload_queue.put(upload_request)
|
||||
echo_log(f"开始推送待办：{dcm_task_id} 的附件数据...")
|
||||
await requests.async_concurrency(
|
||||
upload_queue, con_count=1, retry=dock.MAX_RETRY_COUNT,
|
||||
after_request=after_attachment_upload
|
||||
)
|
||||
|
||||
|
||||
async def upload_with_attachment(fetch_size: int = 50,
|
||||
task_id: Optional[Union[str, int, list[Union[str, int]]]] = None):
|
||||
"""
|
||||
推送附件数据。
|
||||
:param fetch_size: 本次推送数量
|
||||
:param task_id: 待办任务 ID 可选
|
||||
:return:
|
||||
"""
|
||||
from dock.dcm import dcm_api
|
||||
# 根据条件获取目标任务 ID 列表（支持指定 task_id 或分页获取）
|
||||
task_query = select(DcmTask.id).order_by(desc(DcmTask.act_id))
|
||||
if task_id:
|
||||
if isinstance(task_id, list):
|
||||
task_query = task_query.where(DcmTask.id.in_(task_id))
|
||||
echo_log(f"本次上传待办列表：{task_id} 的附件...")
|
||||
else:
|
||||
task_query = task_query.where(DcmTask.id == task_id)
|
||||
echo_log(f"本次上传待办：{task_id} 的附件...")
|
||||
else:
|
||||
task_query = task_query.limit(fetch_size)
|
||||
echo_log(f"本次上传前 {fetch_size} 条附件...")
|
||||
task_id_list = (await DcmTask.orm_execute_scalars(task_query)).all()
|
||||
task_id_list = [f"{id}" for id in task_id_list]
|
||||
|
||||
# 查询属于这些任务的所有附件信息
|
||||
query = select(
|
||||
DcmTaskAttachment.id, DcmTaskAttachment.dcm_task_id,
|
||||
DcmTaskAttachment.media_id, DcmTaskAttachment.media_url
|
||||
).where(
|
||||
DcmTaskAttachment.dcm_task_id.in_(task_id_list)
|
||||
)
|
||||
|
||||
# 生产环境过滤掉已成功上传的附件（避免重复上传）
|
||||
if apps.get_active_env() == 'prod':
|
||||
# 生产环境，不上传已经成功上传的附件文件
|
||||
query = query.where(~exists().where(
|
||||
(DcmTaskFileUpload.dcm_task_attachment_id == DcmTaskAttachment.id) &
|
||||
(DcmTaskFileUpload.status == 1)
|
||||
))
|
||||
else:
|
||||
echo_log(f"非生产环境，上传所有附件.")
|
||||
|
||||
attachment_df = await DcmTaskAttachment.query_as_df(query)
|
||||
# 格式化为字符串
|
||||
attachment_df[DcmTaskAttachment.id.key] = attachment_df[DcmTaskAttachment.id.key].astype(str)
|
||||
attachment_df[DcmTaskAttachment.dcm_task_id.key] = attachment_df[DcmTaskAttachment.dcm_task_id.key].astype(str)
|
||||
|
||||
# 增加文件下载路径列
|
||||
attachment_df[file_url_column_name] = attachment_df.apply(
|
||||
lambda x: f"/{x.get(DcmTaskAttachment.media_url.key).lstrip('/')}"
|
||||
if pd.notna(x.media_url) and str(x.media_url).strip() else "",
|
||||
axis=1
|
||||
)
|
||||
|
||||
# 处理无待办工单上传状态
|
||||
empty_task_ids = set(task_id_list) - set(attachment_df[DcmTaskAttachment.dcm_task_id.key].unique().tolist())
|
||||
empty_task_data = [
|
||||
{
|
||||
DcmPushStatus.dcm_task_id.key: dcm_task_id,
|
||||
DcmPushStatus.push_task_file_upload_status.key: 1
|
||||
}
|
||||
for dcm_task_id in list(empty_task_ids)
|
||||
]
|
||||
empty_task_df = pd.DataFrame(empty_task_data)
|
||||
await DcmPushStatus.save_batch(empty_task_df)
|
||||
|
||||
echo_log(f"正在准备下载队列...")
|
||||
# 创建下载请求，填充请求队列
|
||||
attachment_download_queue = asyncio.Queue()
|
||||
for _h, _row in attachment_df.iterrows():
|
||||
download_request = await dcm_api.new_api_request(_row.get(file_url_column_name), {}, method='GET')
|
||||
setattr(download_request, 'dcm_task_id', _row.get(DcmTaskAttachment.dcm_task_id.key))
|
||||
setattr(download_request, 'dcm_task_attachment_id', _row.get(DcmTaskAttachment.id.key))
|
||||
setattr(download_request, 'dcm_media_id', _row.get(DcmTaskAttachment.media_id.key))
|
||||
await attachment_download_queue.put(download_request)
|
||||
# 提交附件下载请求
|
||||
await requests.async_concurrency(
|
||||
attachment_download_queue, con_count=dock.CONCURRENCY_COUNT, retry=dock.MAX_RETRY_COUNT,
|
||||
after_request=after_attachment_download, after_done=done_attachment_download
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
from paste.core import aio_pool
|
||||
|
||||
_runner = aio_pool.get_aio_runner()
|
||||
_runner(upload_with_attachment(task_id=2059900525595328517))
|
||||
Reference in New Issue
Block a user