Integrate the ERPNext API with the Python API

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

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Popular ERPNext 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 ERPNext#

ERPNext is an open-source enterprise resource planning (ERP) software that integrates core business functions like accounting, inventory, sales, purchase, and HR management into a single system. With the ERPNext API, you can automate these functions by triggering actions in ERPNext or syncing data with other systems. Pipedream can be a powerful partner here, as it allows you to set up complex integrations and workflows without the need for a dedicated backend. By using Pipedream, you can connect ERPNext with numerous other apps to streamline processes, react to events in real-time, and automate data transfers.

Connect ERPNext#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    erpnext: {
      type: "app",
      app: "erpnext",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `${this.erpnext.$auth.base_url}/api/method/frappe.auth.get_logged_user`,
      auth: {
        username: `${this.erpnext.$auth.api_key}`,
        password: `${this.erpnext.$auth.api_secret}`,
      },
    })
  },
})

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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