Amentum Aerospace

Transforming industries with predictive scientific models. Aviation, space, defence, navigation.

Integrate the Amentum Aerospace API with the Python API

Setup the Amentum Aerospace API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Amentum Aerospace 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 Amentum Aerospace

The Amentum Aerospace API provides programmatic access to a suite of aerospace functionalities, such as satellite tracking, pass predictions, and atmospheric conditions. Leveraging this API, one can automate data collection for space-related projects, enhance satellite monitoring applications, or enrich educational platforms with real-time space data. Pipedream's serverless integration platform allows developers to connect the Amentum API with countless other services, creating custom workflows that can trigger actions, send notifications, or store data based on space events or conditions.

Connect Amentum Aerospace

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    amentum_aerospace: {
      type: "app",
      app: "amentum_aerospace",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://${this.amentum_aerospace.$auth.subdomain}.amentum.io/gebco`,
      headers: {
        "Accept": `application/json`,
        "API-Key": `${this.amentum_aerospace.$auth.api_key}`,
      },
      params: {
        latitude: `-45`,
        longitude: `45`,
      },
    })
  },
})

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}}