Integrate the Everhour API with the Go API

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

Popular Everhour 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 Everhour#

Everhour is a time tracking API that allows you to monitor project hours and manage tasks effectively. With Pipedream, you can automate workflows by integrating Everhour with various apps, streamlining time entry, syncing with project management tools, and generating custom reports. Whether you're consolidating time tracking data for invoicing or keeping project budgets in check, Everhour and Pipedream make a powerful duo for automating your time tracking and project management processes.

Connect Everhour#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    everhour: {
      type: "app",
      app: "everhour",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.everhour.com/users/me`,
      headers: {
        "Content-Type": `application/json`,
        "X-Api-Key": `${this.everhour.$auth.api_token}`,
      },
    })
  },
})

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)
}