Integrate the Google Maps (Places API) API with the Python API

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

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Popular Google Maps (Places API) 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 Google Maps (Places API)#

The Google Maps (Places API) offers detailed information about physical locations, including places of interest, reviews, and other metadata. In Pipedream, you can leverage this API to create dynamic workflows that respond to location data. Whether you're building apps that track asset locations, automate location-based alerts, or provide users with local info, integrating with Google Maps can add a powerful spatial context to your services.

Connect Google Maps (Places API)#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    google_maps_platform: {
      type: "app",
      app: "google_maps_platform",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      method: "post",
      url: `https://maps.googleapis.com/maps/api/place/findplacefromtext/json`,
      params: {
        key: `${this.google_maps_platform.$auth.api_key}`,
        input: `Museum of Contemporary Art Australia`,
        inputtype: `textquery`,
      },
    })
  },
})

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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