Integrate the ConvertAPI API with the Go API

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

Popular ConvertAPI 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.

Overview of ConvertAPI#

ConvertAPI is a powerhouse for online file conversion, enabling you to transform files from one format to another effortlessly. It supports a plethora of file types, from common ones like PDFs and DOCs to more obscure formats. With ConvertAPI on Pipedream, you can automate file conversion tasks, seamlessly integrating them into workflows that trigger on events from other apps or schedules. Imagine converting incoming email attachments, processing uploaded documents, or archiving files in a different format—all happening automatically, in the background.

Connect ConvertAPI#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    convertapi: {
      type: "app",
      app: "convertapi",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://v2.convertapi.com/user`,
      params: {
        Secret: `${this.convertapi.$auth.api_secret}`,
      },
    })
  },
})

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)
}