Integrate the Plecto API with the Go API

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

Popular Plecto 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 Plecto#

The Plecto API allows you to automate the process of data visualization and performance tracking. With Pipedream, you can harness this API to create real-time dashboards, generate reports, and update KPIs automatically. Pipedream's serverless platform makes it simple to connect Plecto with other services, trigger events, process data, and more. Whether you're syncing sales data, updating leaderboards, or notifying teams of their performance, Pipedream offers a robust and flexible way to streamline these workflows.

Connect Plecto#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    plecto: {
      type: "app",
      app: "plecto",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://app.plecto.com/api/v2/members`,
      auth: {
        username: `${this.plecto.$auth.username}`,
        password: `${this.plecto.$auth.password}`,
      },
    })
  },
})

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)
}