Integrate the Big Data Cloud API with the Python API

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

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Popular Big Data Cloud and Python Actions#

Get Time Zone by Location with the Big Data Cloud API

Retrieve time zone data for a specified location. See the documentation

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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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Perform IP Geolocation with the Big Data Cloud API

Obtain a user's location data based on their IP address. See the documentation

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Reverse Geocode with the Big Data Cloud API

Convert a user's coordinates to a human-readable address. See the documentation

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Overview of Big Data Cloud#

The Big Data Cloud API provides a suite of RESTful APIs for IP geolocation and various other data services that can enrich your applications with valuable insights. On Pipedream, you can integrate these APIs into serverless workflows to automate data collection, analysis, and decision-making processes. Whether you're looking to enhance user experience with location-based content, validate user data, or perform any number of data-enrichment tasks, Big Data Cloud can be a go-to resource within your Pipedream workflows.

Connect Big Data Cloud#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    big_data_cloud: {
      type: "app",
      app: "big_data_cloud",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api-bdc.net/data/country-by-ip`,
      params: {
        key: `${this.big_data_cloud.$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}}

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