Snapdocs

The perfect mortgage closing experience Fast, convenient, and error-free, the Snapdocs digital mortgage closing platform delivers a perfect closing experience to every single borrower.

Integrate the Snapdocs API with the Python API

Setup the Snapdocs API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Snapdocs 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.

 
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Overview of Snapdocs

The Snapdocs API enables seamless integration with its real estate closing platform, allowing users to automate document handling, notifications, and scheduling within the real estate closing process. By leveraging the Snapdocs API on Pipedream, you can craft custom workflows that streamline communication between agents, clients, and other stakeholders, orchestrate document management, and sync data across various platforms involved in the transaction process.

Connect Snapdocs

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    snapdocs: {
      type: "app",
      app: "snapdocs",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://${this.snapdocs.$auth.environment}.snapdocs.com/mobile_notary_api/v1/clients`,
      headers: {
        "X-AUTH-TOKEN": `${this.snapdocs.$auth.api_key}`,
      },
    })
  },
})

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}}