GraphHopper

We provide route planning for your application (SaaS). Including a powerful Route Optimization API.

Integrate the GraphHopper API with the Python API

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

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.

 
Try it

Overview of GraphHopper

GraphHopper is a powerful routing engine that leverages OpenStreetMap data to provide various services like route optimization, map matching, and travel time calculation. With the GraphHopper API, you can embed routing capabilities into your apps, automate the creation of efficient travel routes, and analyze spatial data to derive insights on movement patterns. On Pipedream, you can create workflows that harness GraphHopper's features to automate logistics, streamline dispatch systems, and perform geospatial analysis in conjunction with other apps and services.

Connect GraphHopper

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    graphhopper: {
      type: "app",
      app: "graphhopper",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://graphhopper.com/api/1/isochrone`,
      params: {
        key: `${this.graphhopper.$auth.api_key}`,
        point: `{enter_coordinates_here}`,
      },
    })
  },
})

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}}