Corrently
Electricity tariff with a loyalty program allowing every electricity customer to do micro investments into renewable energy generation facilities
Integrate the Corrently API with the Python API
Setup the Corrently API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Corrently and Python remarkably fast. Free for developers.
Popular Corrently 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 Corrently#
The Corrently API offers a suite of services related to green energy, including insights on electricity consumption, cost forecasting, and localized energy generation data. With Corrently, you can pull real-time data to drive sustainability initiatives, create cost-optimization strategies for energy usage, and foster eco-friendly practices. Leveraging this API within Pipedream allows for automated workflows that can turn this data into actionable insights, integrate with smart home devices, manage energy budgets, and even shift usage to times when the grid is greener and electricity cheaper.
Connect Corrently#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
corrently: {
type: "app",
app: "corrently",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.corrently.io/v2.0/stromkonto/balances`,
params: {
account: `${this.corrently.$auth.account}`,
},
})
},
})
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}}