Spondyr

Spondyr is an API that helps developers quickly integrate correspondence template management and distribution functionality into their applications.

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.

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

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

 
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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

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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

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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}}

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Adyen logo
Appcues logo
Bandwidth logo
Checkr logo
ChartMogul logo
Dataminr logo
Gopuff logo
Gorgias logo
LinkedIn logo
Logitech logo
Replicated logo
Rudderstack logo
SAS logo
Scale AI logo
Webflow logo
Warner Bros. logo
Adyen logo
Appcues logo
Bandwidth logo
Checkr logo
ChartMogul logo
Dataminr logo
Gopuff logo
Gorgias logo
LinkedIn logo
Logitech logo
Replicated logo
Rudderstack logo
SAS logo
Scale AI logo
Webflow logo
Warner Bros. logo