如何使用python API列出所有数据流作业

本文介绍了如何使用python API列出所有数据流作业的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我的用例涉及获取项目中存在的所有流数据流作业的作业ID，然后将其取消.更新我的数据流作业的源，然后重新运行.

My use case involves fetching the job id of all streaming dataflow jobs present in my project and cancel it. Update the sources for my dataflow job and re-run it.

我正在尝试使用python实现此目的.到目前为止，我还没有遇到任何有用的文档. 我考虑过使用python的库子进程来执行gcloud命令，这是一种解决方法.但是我还是无法存储结果并使用它.

I am trying to achieve this using python. I did not come across any useful documentation until now. I thought of using python's library subprocess to execute the gcloud commands as a workaround. But again I was not able to store the result and use it.

有人可以指导我，因为这样做的最好方法是什么.

Can somebody please guide me as what is the best way of doing this.

推荐答案

除了直接使用其余的API，您还可以在 google-api-python-client .对于简单的调用，它并没有带来太多的价值，但是当传递许多参数时，它比原始的HTTP库更容易使用.

In addition to using the rest API directly, you can use the generated Python bindings for the API in google-api-python-client. For simple calls it doesn't add that much value, but when passing in many parameters it can be easier to work with than a raw HTTP library.

使用该库，作业列表调用看起来像

With that library, the jobs list call would look like

from googleapiclient.discovery import build import google.auth credentials, project_id = google.auth.default(scopes=['www.googleapis/auth/cloud-platform']) df_service = build('dataflow', 'v1b3', credentials=credentials) response = df_service.projects().locations().jobs().list( project_id=project_id, location='<region>').execute()