Linkly
Easily create tracking links, add retargeting tags, do smart redirects and more.
Integrate the Linkly API with the Python API
Setup the Linkly API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Linkly and Python remarkably fast. Free for developers.
Popular Linkly and Python Actions#
Creates a new Linkly link using the provided URL. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Linkly#
The Linkly API enables you to create and manage short links, track clicks, and analyze the performance of your links in real-time. It's a tool for marketers, developers, and content creators who need to understand user engagement and optimize their online presence. By using Linkly API within Pipedream, you can integrate URL shortening and tracking capabilities into your workflows, allowing for automated link management and data collection. You can build automated processes that trigger on new link creation, analyze click data, generate reports, or sync with other marketing and analytics services to enhance your strategies.
Connect Linkly#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
linkly: {
type: "app",
app: "linkly",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://app.linklyhq.com/api/v1/workspace/${this.linkly.$auth.workspace_id}/list_links`,
params: {
api_key: `${this.linkly.$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}}