Databox
Connect your data from any tool and track it from any device. No more logging into dozens of different tools to understand performance — now you and your team can easily connect your data, build and share reports, monitor trends, and discover insights.
Integrate the Databox API with the Python API
Setup the Databox API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Databox and Python remarkably fast. Free for developers.
Popular Databox and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Databox#
The Databox API enables you to create custom dashboards, integrating various data sources to track performance metrics in real-time. With Pipedream, you can leverage this API to automate the flow of data between Databox and other applications, creating bespoke monitoring solutions and data-driven workflows that save time and enhance insights.
Connect Databox#
import Databox from 'databox'
export default defineComponent({
props: {
databox: {
type: "app",
app: "databox",
},
},
async run({steps, $}) {
const client = new Databox({
push_token: `${this.databox.$auth.token}`
})
return await new Promise((resolve) => client.metrics((metrics) => resolve(metrics)))
}
})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}}