Integrate the Contact Enhance API with the Python API

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

Popular Contact Enhance and Python Actions#

Find Contact with the Contact Enhance API

Locates a specific contact in the database using the email. See the documentation

Try it

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.

Try it

Overview of Contact Enhance#

The Contact Enhance API allows you to enrich contact data by providing detailed information on individuals or companies based on email, domain, or other identifying data. With this API integrated into Pipedream, it's possible to automate enriching contact lists, validate and score leads for marketing, and augment customer profiles for better personalization. Pipedream's serverless platform enables these tasks to be set up with minimal coding, leveraging a vast array of triggers and actions from various apps to create powerful workflows.

Connect Contact Enhance#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    contact_enhance: {
      type: "app",
      app: "contact_enhance",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      method: "post",
      url: `https://contactenhance-91b9c0ef8a71.herokuapp.com/contacts`,
      headers: {
        "Content-Type": `application/json`,
        "Authorization": `${this.contact_enhance.$auth.api_key}`,
      },
      params: {
        email: `email@example.com`,
      },
    })
  },
})

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}}