Unbounce
Unbounce landing pages have helped businesses turn billions of visitors into leads, sales, and signups. (Literally.) Combining that data with AI, Unbounce lets you create custom landing pages twice as fast as old-school builders.
Integrate the Unbounce API with the Python API
Setup the Unbounce API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Unbounce and Python remarkably fast. Free for developers.
Popular Unbounce and Python Triggers#
Emit new event when a new form submit is received.
Popular Unbounce and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Retrieve a list of all leads for a given page (including AMP), pop-up, or sticky-bar. See the documentation
Overview of Unbounce#
The Unbounce API lets you tap into the powerful landing page platform to automate tasks and sync data with other services. Use it within Pipedream workflows to capture, analyze, and act on leads generated through your landing pages. Think of fetching form submissions, updating leads in a CRM, or dynamically modifying landing page content.
Connect Unbounce#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
unbounce: {
type: "app",
app: "unbounce",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.unbounce.com/users/self`,
headers: {
Authorization: `Bearer ${this.unbounce.$auth.oauth_access_token}`,
"Accept": `application/vnd.unbounce.api.v0.4+json`,
},
})
},
})
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}}