Integrate the Shorten.REST API with the Python API

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

Popular Shorten.REST and Python Actions#

Get Clicks with the Shorten.REST API

Gets the click data. 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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Shorten Link with the Shorten.REST API

Shortens a given long URL into an alias. If the alias name is not provided, the system generates one. If the domain input is not provided, it defaults to short.fyi. See the documentation

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Overview of Shorten.REST#

Shorten.REST API on Pipedream allows you to automate URL shortening, expanding, and tracking within your custom workflows. With this API, you can create short, branded links programmatically, obtain detailed analytics on click-throughs, and manage your URLs efficiently, all within Pipedream's serverless platform. This enables seamless integration of URL management into your applications, marketing campaigns, or day-to-day tasks while leveraging various triggers and actions from other apps available on Pipedream.

Connect Shorten.REST#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    shorten_rest: {
      type: "app",
      app: "shorten_rest",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.shorten.rest/clicks`,
      headers: {
        "Content-Type": `application/json`,
        "x-api-key": `${this.shorten_rest.$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#

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}}