Integrate the AnnounceKit API with the Python API

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

Popular AnnounceKit 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.

Try it

Overview of AnnounceKit#

AnnounceKit is a tool for creating, managing, and publishing announcements to keep your users informed about product updates and news. Using the AnnounceKit API within Pipedream, you can automate the delivery of these updates across different platforms, sync release notes with your product's lifecycle events, or control the flow of communication based on user behavior or preferences. This level of automation can enhance user engagement and ensure timely updates without manual intervention.

Connect AnnounceKit#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    announcekit: {
      type: "app",
      app: "announcekit",
    }
  },
  async run({steps, $}) {
    const data = {
      "query": `{ 
     me { 
      active_project {
        id
        name
      }
     } 
    }`,
    }
    return await axios($, {
      method: "post",
      url: `https://announcekit.app/gq/v2`,
      headers: {
        "Content-Type": `application/json`,
      },
      auth: {
        username: `${this.announcekit.$auth.email}`,
        password: `${this.announcekit.$auth.password}`,
      },
      data,
    })
  },
})

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}}