TurboHire

Integrate the TurboHire API with the Go API

Setup the TurboHire API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate TurboHire 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 TurboHire

TurboHire is a talent acquisition platform that streamlines the hiring process using automation and AI. With its API, you can enrich candidate profiles, automate communication, and trigger actions based on recruitment stages. On Pipedream, you can leverage TurboHire’s API to create powerful automations by connecting it to a multitude of services, thus enhancing the hiring workflow, maintaining candidate databases, and ensuring timely interactions.

Connect TurboHire

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    turbohire: {
      type: "app",
      app: "turbohire",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.turbohire.co/api/jobs/:job-id`,
      headers: {
        "X-Api-Key": `${this.turbohire.$auth.api_key}`,
        "Content-Type": `application/json`,
      },
      params: {
        "job-id": `{{Job-ID}}`,
      },
    })
  },
})

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)
}