Integrate the Modern Treasury API with the Python API

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

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Popular Modern Treasury and Python Actions#

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 Modern Treasury#

Modern Treasury is a powerful platform for payment operations, allowing businesses to manage payments, banking, and reconciliation easily. Through its API, you can initiate transfers, update transactions, reconcile accounts, and automate workflows related to financial transactions. Pipedream, as a serverless integration and compute platform, empowers you to connect Modern Treasury with countless other apps to create custom automation workflows, trigger actions based on payment events, and synchronize financial data across your business systems.

Connect Modern Treasury#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    modern_treasury: {
      type: "app",
      app: "modern_treasury",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://app.moderntreasury.com/api/api_keys/current`,
      auth: {
        username: `${this.modern_treasury.$auth.organization_id}`,
        password: `${this.modern_treasury.$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}}

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