Ramp

The Corporate Card That Helps You Spend Less

Integrate the Ramp API with the Python API

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

Run Python Code with Python API on New Transactions from Ramp API
Ramp + Python
 
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New Transactions from the Ramp API

Emit new transaction by retrieving all transactions of the business. See Docs

 
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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 Ramp

The Ramp API provides programmatic access to financial and accounting functionalities, allowing for the management of company cards, transactions, and reporting. By leveraging the Ramp API within Pipedream, you can automate intricate finance operations, synchronize transaction data with accounting software, trigger notifications based on spending activities, and analyze financial data in real-time, integrating with other services for enhanced financial workflows.

Connect Ramp

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    ramp: {
      type: "app",
      app: "ramp",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.ramp.com/developer/v1/business`,
      headers: {
        Authorization: `Bearer ${this.ramp.$auth.oauth_access_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}}