Integrate the Spondyr API with the Python API

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

Popular Ways to Connect Spondyr with Python#

Run Python Code with Python API on New Spondyr Processed from Spondyr API

Spondyr + Python

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Popular Spondyr and Python Triggers#

New Spondyr Processed from the Spondyr API

Emit new event when a spondyr is processed. See docs here

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Popular Spondyr and Python Actions#

Create Spondyr with the Spondyr API

Generate and optionally deliver correspondence. See the docs here

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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.

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Overview of Spondyr#

The Spondyr API, known as MailboxValidator, is a tool designed to clean and verify email lists, ensuring that businesses can keep their email marketing databases free of invalid, inactive, or disposable email addresses. By integrating Spondyr with Pipedream, you can automate the process of maintaining a high-quality email list, triggering email validation workflows, and integrating with other services to enhance user management, campaign effectiveness, and overall data hygiene.

Connect Spondyr#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    spondyr: {
      type: "app",
      app: "spondyr",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://client.spondyr.io/api/v1.0.0/TransactionTypes`,
      params: {
        APIKey: `${this.spondyr.$auth.api_key}`,
        ApplicationToken: `${this.spondyr.$auth.app_token}`,
      },
    })
  },
})

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}}