Givebutter
#1 rated, world's first free fundraising platform powering $150M+ in donations annually for thousands of good causes. đź’›
Integrate the Givebutter API with the Python API
Setup the Givebutter API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Givebutter and Python remarkably fast. Free for developers.
Popular Givebutter 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 Givebutter#
The Givebutter API taps into the platform's fundraising capabilities, allowing developers to manage campaigns, track donations, and engage with supporters. It's designed for nonprofits and community organizations looking to automate their fundraising efforts and integrate with other services for a seamless workflow. By leveraging the Givebutter API on Pipedream, one can create custom automations that sync data between tools, send real-time notifications, and analyze fundraising activities without manual input, ensuring that resources are focused on the mission rather than administrative tasks.
Connect Givebutter#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
givebutter: {
type: "app",
app: "givebutter",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.givebutter.com/v1/contacts`,
headers: {
Authorization: `Bearer ${this.givebutter.$auth.api_key}`,
"Accept": `application/json`,
},
})
},
})
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}}