zwf
59 lines
2.3 KiB
Python
59 lines
2.3 KiB
Python
import asyncio
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import json
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import pandas as pd
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from tornado.httpclient import HTTPResponse, HTTPRequest
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from dock.govc import govc_api
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import models
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from models.govc_task_process import GovcTaskProcess
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from paste.util import udict
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from paste.core.logging import echo_log
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async def get_process_request(pviguid: str, cguid: str):
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"""
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获取市12345的工单的办理过程信息，请求响应是单条工单的数据
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:param pviguid: 工单列表请求返回的pviguid
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:param cguid: 工单列表请求返回的cguid
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"""
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api_url = '/rest/sztaskworkordercommonrest/getTracing'
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headers = {
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'Referer': f'{govc_api.ApiUrl}/rest/sztaskworkordercommonrest/getTracing'
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}
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request_body = {
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'caseguid': cguid,
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'pviguid': pviguid
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}
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# 构造 API 请求
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return await govc_api.new_api_request(api_url, request_body, headers=headers, method='GET')
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async def after_process_request(response: HTTPResponse, retry_queue: asyncio.Queue[HTTPRequest]):
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"""
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任务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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response_body = response.body.decode()
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response_data = json.loads(response_body)
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process_list = udict.get_by_path(response_data, 'params.processedList')
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if process_list:
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mapped_df = pd.DataFrame(process_list)
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# 更换映射方向，用于将源数据列名改为与数据库表对应
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forward_mapping = {dict_f: table_f for table_f, dict_f in GovcTaskProcess.FieldMapping.items()}
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mapped_df = mapped_df.rename(columns=forward_mapping)
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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, None, inplace=True)
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task_id = getattr(response.request, GovcTaskProcess.task_id.key)
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mapped_df[GovcTaskProcess.task_id.key] = task_id
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# 筛选数据状态
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_created, _updated = await GovcTaskProcess.save_batch(mapped_df)
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echo_log(f"成功创建办理过程信息：{_created}条，更新：{_updated}条.")
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else:
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echo_log('未获取到办理过程信息')
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if retry_queue:
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echo_log(f"办理过程信息重试队列中有：{retry_queue.qsize()} 个请求在等待.")
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