Integrate the IdealSpot API with the Python API

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

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Popular IdealSpot and Python Actions#

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 IdealSpot#

The IdealSpot API allows users to access valuable geolocation data to inform business decision-making. With this API, you can obtain insights on foot traffic, demographic profiles, competitive landscapes, and commercial real estate availability. It's a powerful tool for businesses looking to analyze and optimize site selection for physical locations. By leveraging the IdealSpot API on Pipedream, you can automate and enhance data-driven decisions, seamlessly integrating this rich geolocation data with other business applications, streamlining workflows, and gaining real-time market intelligence.

Connect IdealSpot#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    idealspot: {
      type: "app",
      app: "idealspot",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://idealspot-geodata.p.rapidapi.com/api/v1/traffic/counts/1595369397`,
      headers: {
        "X-RapidAPI-Key": `${this.idealspot.$auth.api_key}`,
        "X-RapidAPI-Host": `idealspot-geodata.p.rapidapi.com`,
      },
    })
  },
})

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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