PingBell

Instantly notify your entire team each time a conversion happens on your website or app

Integrate the PingBell API with the Python API

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

Send Notification with the PingBell API

Sends a notification to a Pingbell. See the documentation

 
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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 PingBell

The PingBell API is a versatile tool for automating interactions with your physical PingBell device. Pipedream, a serverless integration and compute platform, helps you build workflows around the PingBell API with ease. You can craft automations that trigger when someone rings your PingBell, check the device's battery level, and much more, all within Pipedream's simplified workflow environment. By using Pipedream's capabilities, you can integrate with various apps, send notifications through different channels, log data, and implement complex logic to respond to PingBell events.

Connect PingBell

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    pingbell: {
      type: "app",
      app: "pingbell",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://app.pingbell.io/userPingbells`,
      params: {
        api_key: `${this.pingbell.$auth.api_key}`,
      },
    })
  },
})

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

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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}}