Solcast
Solar resource assessment and forecasting data for irradiance and PV power, globally.
Integrate the Solcast API with the Python API
Setup the Solcast API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Solcast and Python remarkably fast. Free for developers.
Popular Solcast 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 Solcast#
The Solcast API offers solar energy forecasting and historical solar data, enabling developers to integrate accurate solar radiation, PV power output, and weather data into their applications. With the Solcast API on Pipedream, you can automate data retrieval for solar project planning, performance monitoring, and energy system integration. Pipedream's serverless platform means you can set up workflows that respond to various triggers to process and act on Solcast data in real-time, without managing infrastructure.
Connect Solcast#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
solcast: {
type: "app",
app: "solcast",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.solcast.com.au/data/forecast/radiation_and_weather`,
headers: {
Authorization: `Bearer ${this.solcast.$auth.api_key}`,
"Accept": `application/json`,
},
params: {
latitude: `-33.856784`,
longitude: `151.215297`,
output_parameters: `air_temp,dni,ghi`,
},
})
},
})
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}}