Integrate the Vryno API with the Python API

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

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Popular Vryno and Python Actions#

Create Unique Lead with the Vryno API

Creates a unique lead in the Vryno system, ensuring no duplication of lead details. See the documentation

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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 Vryno#

The Vryno API provides functionality to access a platform that specializes in various services including but not limited to real estate, healthcare, and educational services. By integrating this API into Pipedream workflows, developers can automate interactions and data exchanges between Vryno and other platforms, enhancing efficiency and enabling innovative service delivery models.

Connect Vryno#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    vryno: {
      type: "app",
      app: "vryno",
    }
  },
  async run({steps, $}) {
    const data = {
    "query": "{ fetchBulkImportJob { code  messageKey  data{ id  fileName } } }"
    }
    return await axios($, {
      method: "post",
      url: `https://${this.vryno.$auth.company_instance_name}.ms.vryno.com/api/graphql/crm`,
      headers: {
        Authorization: `Bearer ${this.vryno.$auth.oauth_access_token}`,
      },
      data,
    })
  },
})

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}}

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