Integrate the Klipfolio API with the Python API

Klipfolio

Klipfolio is the new way everyday people and their teams make informed decisions, backed by data. Klipfolio is a data analytics cloud app for building and sharing real-time business dashboards and reports on web browsers, TV monitors and mobile devices. Klipfolio helps you stay in-the-know and in control of your business by giving you visibility into the KPIs and metrics that matter most.

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

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Popular Klipfolio 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 Klipfolio#

The Klipfolio API opens a window to managing and automating your Klipfolio dashboards and data sources directly from Pipedream. With this API, you can programmatically create, update, and delete dashboards, Klips (widgets), and data sources. This allows you to integrate Klipfolio with a multitude of other services, triggering updates to your dashboards as data changes in other apps, or even automate the import and transformation of data for your Klipfolio visualizations.

Connect Klipfolio#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    klipfolio: {
      type: "app",
      app: "klipfolio",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://app.klipfolio.com/api/1.0/profile`,
      headers: {
        "kf-api-key": `${this.klipfolio.$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}}

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