Integrate the CloudBees API with the Python API

CloudBees

Every business is a software business, and is under pressure to innovate constantly. This increased velocity introduces new business risks. CloudBees (www.cloudbees.com) is building the world’s first end-to-end automated software delivery system, enabling companies to balance governance and developer freedom.

Setup the CloudBees API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate CloudBees and Python remarkably fast. Free for developers.

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Popular CloudBees and Python Actions#

Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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Overview of CloudBees#

The CloudBees API interfaces with CloudBees CI and CD solutions to automate and manage build, test, and deployment processes for software projects. Through integration with Pipedream, you can harness the potential of the CloudBees API to create custom workflows. This might include triggering deployments, managing build statuses, or responding to events within your CI/CD pipeline. Automating these tasks can expedite the development cycle, reduce errors, and enhance productivity.

Connect CloudBees#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    cloudbees: {
      type: "app",
      app: "cloudbees",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://x-api.rollout.io/public-api/users`,
      headers: {
        Authorization: `Bearer ${this.cloudbees.$auth.api_token}`,
        "Content-Type": `application/json`,
      },
    })
  },
})

Overview of Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}

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