Make something useful with data from the Norwegian Meteorological Institute
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
The Yr API provides meteorological data, allowing you to access weather forecasts, historical data, and various meteorological elements for locations worldwide. On Pipedream, you can leverage this data in serverless workflows, creating custom automations that react to weather changes, integrate with other services, or provide timely weather updates.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
yr: {
type: "app",
app: "yr",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.met.no/weatherapi/locationforecast/2.0/compact`,
headers: {
"User-Agent": `pipedream.com`,
},
params: {
lat: `51.5`,
lon: `0`,
},
})
},
})
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:
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}}