如何使用python API列出所有数据流作业 [英] How to list down all the dataflow jobs using python API

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

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=['https://www.googleapis.com/auth/cloud-platform'])
df_service = build('dataflow', 'v1b3', credentials=credentials)
response = df_service.projects().locations().jobs().list(
  project_id=project_id,
  location='<region>').execute()

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