ipdata.co

Enrich IP Addresses with Location, Company, Carrier & Threat Data

Integrate the ipdata.co API with the Python API

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

GET /{ip_address} with the ipdata.co API

Lookup a specific IP Address

 
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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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GET /carrier/{ip_address} with the ipdata.co API

The ipdata API supports looking up the Mobile Carrier of an IP Address. Our database currently consists of over 2500 carriers in 234 countries. https://docs.ipdata.co/overview/mobile-carrier-detection

 
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GET /time_zone/{ip_address} with the ipdata.co API

We provide detailed and accurate Timezone data, adjusted for DST where necessary. https://docs.ipdata.co/overview/timezone-detection

 
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Overview of ipdata.co

The ipdata.co API allows you to enrich IP addresses with geolocation and other relevant data points. With this API integrated into Pipedream, you can automate actions based on the physical location or details of an IP address. This enables a wide range of applications such as customizing content based on user location, flagging fraudulent activity, or tailoring marketing campaigns to specific regions.

Connect ipdata.co

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    ipdata_co: {
      type: "app",
      app: "ipdata_co",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.ipdata.co?api-key=${this.ipdata_co.$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

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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}}