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.

Send Custom Data with the Databox API

Sends custom data. 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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Overview of Databox

You can use the Databox API to build a variety of applications, including:

  • A dashboard for tracking your business performance
  • A data visualization tool for exploring your data
  • A report builder for creating custom reports
  • An alerts system for monitoring your data in real-time
  • A data management tool for organizing your data

Connect Databox

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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

Python API on Pipedream offers developers to build or automate a variety of
tasks from their web and cloud apps. With the Python API, users are able to
create comprehensive and flexible scripts, compose and manage environment
variables, and configure resources to perform a range of functions.

By using Pipedream, you can easily:

  • Create automated workflows that run on a specific schedule
  • Compose workflows across various apps and services
  • React to events in cloud services or form data
  • Automatically create content and notifications
  • Construct classifications and predictions
  • Analyze and react to sentiment, sentiment analysis and sentiment score
  • Connect backends to the frontend with serverless functions
  • Work with files and databases
  • Perform web requests and fetch data
  • Integrate third-party APIs into your apps
  • Orchestrate data processing tasks and pipelines
  • Create powerful application APIs with authentication and authorization
  • Design CI/CD pipelines and Continuous Delivery services
  • Connect databases like MongoDB and MySQL
  • Monitor connections and events
  • Generate alerts and notifications for corresponding events

Connect Python

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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}}