T2M URL Shortener

Whether you are a bubbling startup or an established behemoth MNC organisation, T2M is your go to destination for all kinds of URL marketing endeavors.

Integrate the T2M URL Shortener API with the Python API

Setup the T2M URL Shortener API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate T2M URL Shortener and Python remarkably fast. Free for developers.

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 T2M URL Shortener

The T2M URL Shortener API lets you shorten URLs, manage them, and track analytics within Pipedream's automated workflows. By integrating with Pipedream, you can create shortened URLs on the fly, update them, and get click data without manual intervention. This capability is especially useful for marketing, content distribution, and social media management, where streamlined URL management can be seamlessly embedded into broader automated tasks.

Connect T2M URL Shortener

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    t2m_url_shortener: {
      type: "app",
      app: "t2m_url_shortener",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://t2mio.com/api/v1/urls`,
      headers: {
        "apikey": `${this.t2m_url_shortener.$auth.api_key}`,
        "apisecret": `${this.t2m_url_shortener.$auth.api_secret}`,
      },
    })
  },
})

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}}