Melissa Data

Melissa specializes in global contact data quality and mailing preparation solutions for both small businesses and large enterprises.

Integrate the Melissa Data API with the Python API

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

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 Melissa Data

The Melissa Data API provides data quality services that can validate, cleanse, append, and enrich your data. Using Pipedream, you can seamlessly integrate these capabilities into workflows, automating processes that require address verification, email validation, phone number validation, and more. With Pipedream's serverless platform, you can trigger workflows with HTTP requests, schedule them, or even run them in response to events from other apps.

Connect Melissa Data

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    melissa_data: {
      type: "app",
      app: "melissa_data",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://globalip.melissadata.net/v4/web/iplocation/doiplocation`,
      params: {
        id: `${this.melissa_data.$auth.api_key}`,
        ip: `47.149.180.9`,
      },
    })
  },
})

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

1
2
3
4
5
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}}