GivingFuel

The world’s simplest and most affordable donation platform, GivingFuel helps people and organizations fundraise to change the world.

Integrate the GivingFuel API with the Go API

Setup the GivingFuel API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate GivingFuel and Go remarkably fast. Free for developers.

Run Go Code with the Go API

Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.

 
Try it

Overview of GivingFuel

The GivingFuel API enables non-profit organizations to automate their donation processes, manage donor information, and analyze donation data directly within Pipedream. By leveraging this API, you can create workflows that streamline the collection and use of donation information, trigger actions based on donation events, and integrate with other apps to enrich the donor's journey or facilitate the management of fundraising campaigns.

Connect GivingFuel

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    givingfuel: {
      type: "app",
      app: "givingfuel",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.webconnex.com/v2/public/ping`,
      params: {
        apiKey: `${this.givingfuel.$auth.api_key}`,
      },
    })
  },
})

Overview of Go

You can execute custom Go scripts on-demand or in response to various triggers and integrate with thousands of apps supported by Pipedream. Writing with Go on Pipedream enables backend operations like data processing, automation, or invoking other APIs, all within the Pipedream ecosystem. By leveraging Go's performance and efficiency, you can design powerful and fast workflows to streamline complex tasks.

Connect Go

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package main

import (
	"fmt"

	pd "github.com/PipedreamHQ/pipedream-go"
)

func main() {
	// Access previous step data using pd.Steps
	fmt.Println(pd.Steps)

	// Export data using pd.Export
	data := make(map[string]interface{})
	data["name"] = "Luke"
	pd.Export("data", data)
}