Expedy
Expedy is an online SaaS software suite: IOT Cloud Print | TMS & Automation (API) Cloud Print; Transport Management System.
Integrate the Expedy API with the Python API
Setup the Expedy API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Expedy and Python remarkably fast. Free for developers.
Popular Expedy and Python Actions#
Sends a print job to the designated thermal printer using its unique identifier (uid). See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Expedy#
The Expedy API provides a platform for automating the management of expenses, allowing you to upload receipts, categorize expenses, and generate reports. By leveraging the Expedy API within Pipedream, you can create serverless workflows that handle various aspects of expense tracking and report generation, without the need to manage infrastructure. This can lead to a significant reduction in manual work, increasing efficiency for individuals or finance teams.
Connect Expedy#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
expedy: {
type: "app",
app: "expedy",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://www.expedy.fr/api/v2/printers/all`,
headers: {
"Accept": `application/json`,
"Authorization": `${this.expedy.$auth.api_sid}:${this.expedy.$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}}