AerisWeather

AerisWeather provides a powerful weather API, mapping platform, and developer toolkits that allow weather-sensitive businesses worldwide to operate more efficiently, safely, and profitably.

Integrate the AerisWeather API with the Python API

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

AerisWeather API offers a vast array of weather data, from current conditions to forecasts and severe weather alerts. Harnessing this data through Pipedream allows for the creation of personalized, automated workflows that react to weather updates in real-time. Whether it's triggering alerts based on weather changes, integrating with smart home systems, or optimizing business operations based on climatic conditions, AerisWeather's rich data sets open up a world of possibilities for automation on Pipedream.

Connect AerisWeather

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    aerisweather: {
      type: "app",
      app: "aerisweather",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `http://api.aerisapi.com/observations/seattle%2Cwa`,
      params: {
        client_id: `${this.aerisweather.$auth.app_id}`,
        client_secret: `${this.aerisweather.$auth.app_secret}`,
      },
    })
  },
})

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}}