Integrate the DealMachine API with the Python API

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

Popular Ways to Connect DealMachine with Python#

Run Python Code with Python API on New Lead from DealMachine API

DealMachine + Python

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Popular DealMachine and Python Triggers#

New Lead from the DealMachine API

Emit new event when a new lead is created.

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Popular DealMachine and Python Actions#

Add Lead with the DealMachine API

Add a lead to your team's account. 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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Add Tags to Lead with the DealMachine API

Add tags(s) to the lead. See the documentation

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Create Note with the DealMachine API

Create a note for the lead. See the documentation

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Overview of DealMachine#

The DealMachine API allows for automation of real estate investment tasks such as property research, direct mail marketing, and lead management. By connecting the DealMachine API to Pipedream, users can automate workflows, combine real estate data with other apps, and trigger custom actions based on specific criteria. Pipedream's serverless platform provides a powerful way to interact with the DealMachine API, process data, and integrate with countless other services to optimize real estate investment strategies.

Connect DealMachine#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    dealmachine: {
      type: "app",
      app: "dealmachine",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.dealmachine.com/public/v1/team-members/`,
      headers: {
        Authorization: `Bearer ${this.dealmachine.$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#

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}}