Integrate the Feedier API with the Go API

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

Popular Feedier and Go Actions#

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 Feedier#

The Feedier API lets you harness the power of customer feedback by automating the collection and analysis process. With this API, you can create, retrieve, update, and delete feedback, along with managing carriers and rewards. It enables you to streamline the feedback loop, integrate with your CRM, and trigger actions based on customer responses. Pipedream's serverless platform opens up a world of possibilities for integrating Feedier with hundreds of other apps to automate workflows, analyze data, and respond in real-time to customer insights.

Connect Feedier#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    feedier: {
      type: "app",
      app: "feedier",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.feedier.com/v1/carriers`,
      headers: {
        Authorization: `Bearer ${this.feedier.$auth.api_private_key}`,
        "Accept": `application/json`,
        "Cache-Control": `no-cache`,
      },
    })
  },
})

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#

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)
}