LeadBoxer
Lead generation platform that gives you real-time info about companies and people that visit your website. Turning anonymous web traffic into actionable data.
Integrate the LeadBoxer API with the Python API
Setup the LeadBoxer API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate LeadBoxer and Python remarkably fast. Free for developers.
Popular LeadBoxer and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of LeadBoxer#
The LeadBoxer API lets you track and score leads using web and email behavior data. With this API on Pipedream, you can automate the collection of lead insights, trigger actions based on lead scores or activities, and integrate this data into your CRM or other business tools. By tapping into webhooks and Pipedream's serverless platform, you can create workflows that react in real-time to lead interactions, enrich lead profiles, or sync information across multiple services.
Connect LeadBoxer#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
leadboxer: {
type: "app",
app: "leadboxer",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://kibana.leadboxer.com/api/views/c_view_leads`,
headers: {
"Content-Type": `application/json`,
},
params: {
apiKey: `${this.leadboxer.$auth.api_key}`,
site: `${this.leadboxer.$auth.dataset_id}`,
},
})
},
})
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}}