with Expensify and Python?
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Creates a new report with transactions in a user's account. See docs here
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.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
expensify: {
type: "app",
app: "expensify",
}
},
async run({ steps, $ }) {
// The Expensify API requires the request data to be sent as
// a URL-encoded form with a key of "requestJobDescription".
// The value of this key must be a JSON string.
// First, define the JSON object as per the Expensify API documentation.
const requestJobDescription = {
type: "get",
credentials: {
partnerUserID: this.expensify.$auth.partnerUserId,
partnerUserSecret: this.expensify.$auth.partnerUserSecret,
},
inputSettings: {
type: "policyList",
}
};
// Use URLSearchParams to create a properly formatted form body.
const formData = new URLSearchParams();
formData.append('requestJobDescription', JSON.stringify(requestJobDescription));
// Make the API call with the correctly formatted data.
return await axios($, {
method: "post",
url: `https://integrations.expensify.com/Integration-Server/ExpensifyIntegrations`,
data: formData,
// It's good practice to explicitly set the Content-Type header
// to match the data format.
headers: {
'Content-Type': 'application/x-www-form-urlencoded',
},
});
},
})
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:
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}}