Integrate the Expensify API with the Python API

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

Popular Expensify and Python Actions#

Create Expense with the Expensify API

Creates a new expense. See docs here

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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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Export Report To PDF with the Expensify API

Export a report to PDF. See docs here

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Overview of Expensify#

The Expensify API enables the automation of expense reporting and management tasks. By harnessing this API within Pipedream, you can craft workflows that streamline the expense submission process, synchronize financial data across platforms, and trigger actions based on expense report statuses. With Pipedream’s serverless platform, these automations can run in the background, allowing for real-time data processing and interaction between Expensify and a myriad of other apps and services.

Connect Expensify#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    expensify: {
      type: "app",
      app: "expensify",
    }
  },
  async run({steps, $}) {
    const requestBody = 
      `requestJobDescription={
        "type":"get",
        "credentials":{
            "partnerUserID": "${this.expensify.$auth.partnerUserId}",
            "partnerUserSecret": "${this.expensify.$auth.partnerUserSecret}"
        },
        "inputSettings":{
            "type":"policyList",
        }
      }`
    return await axios($, {
      method: "post",
      url: `https://integrations.expensify.com/Integration-Server/ExpensifyIntegrations`,
      data: requestBody,
    })
  },
})

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}}