Pirate Weather
A Free, Open, and Documented Forecast API A weather forecast API, built as a compatible alternative to the Dark Sky API.
Integrate the Pirate Weather API with the Python API
Setup the Pirate Weather API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Pirate Weather and Python remarkably fast. Free for developers.
Popular Pirate Weather and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Pirate Weather#
The Pirate Weather API delivers accurate weather forecasts, leveraging the same data model as top-tier weather services. Within Pipedream, you can craft workflows that tap into this forecast data to trigger events, power notifications, or feed into data analytics tools. The serverless nature of Pipedream simplifies the process of setting up these workflows, allowing for easy integration with various services for a myriad of applications ranging from personal alerts to data driven decision-making in business.
Connect Pirate Weather#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
pirate_weather: {
type: "app",
app: "pirate_weather",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.pirateweather.net/forecast/${this.pirate_weather.$auth.api_key}/{your_lat,your_long}`,
})
},
})
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#
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}}