What do you want to automate
with Klipfolio and Python?
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Popular Klipfolio and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Delete the data source associated with a specific data source ID. See the documentation
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}}Trusted by 1,000,000+ developers from startups to Fortune 500 companies