Ambient Weather

Ambient Weather is the market leader in weather station and environmental monitoring instruments and the cloud. Ambient Weather is a Nielsen-Kellerman Company.

Integrate the Ambient Weather API with the Python API

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

The Ambient Weather API provides real-time access to personal weather station data, enabling you to monitor and analyze environmental conditions. Through Pipedream's integration, you can automate actions based on this data, such as triggering alerts when specific weather thresholds are reached, logging climate trends for analysis, or controlling smart home devices to adapt to changing conditions.

Connect Ambient Weather

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    ambient_weather: {
      type: "app",
      app: "ambient_weather",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://${this.ambient_weather.$auth.subdomain}.ambientweather.net/v1/devices`,
      params: {
        applicationKey: `${this.ambient_weather.$auth.application_key}`,
        apiKey: `${this.ambient_weather.$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}}