Integrate the Gupshup API with the Go API

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

Popular Gupshup 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 Gupshup#

The Gupshup API enables developers to build communication solutions with extensive messaging capabilities. On Pipedream, you can harness this power to create serverless workflows that interact with Gupshup's messaging services. Automate sending messages, create chatbots, or build complex communication systems that react to incoming messages or events. The workflows can be triggered by webhooks, schedules, or other apps' events, and you can integrate Gupshup with numerous other services available on Pipedream.

Connect Gupshup#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    gupshup: {
      type: "app",
      app: "gupshup",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.gupshup.io/sm/api/v1/users/${this.gupshup.$auth.appname}`,
      headers: {
        "apikey": `${this.gupshup.$auth.apikey}`,
      },
    })
  },
})

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)
}