Integrate the Crowdin API with the Go API

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

Popular Crowdin 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 Crowdin#

The Crowdin API offers a way to streamline localization processes by enabling automated interactions with Crowdin projects. With this API on Pipedream, you can create workflows that manage translations, coordinate with translators, and sync localized content across your apps. It becomes easy to upload new source files, download translations, manage projects, and crowdsource translations, all within the Pipedream ecosystem.

Connect Crowdin#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    crowdin: {
      type: "app",
      app: "crowdin",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      // If you are using Crowdin Enterprise, your API URL
      // should be https://{your_org_domain}.api.crowdin.com/
      url: `https://api.crowdin.com/api/v2/user`,
      headers: {
        Authorization: `Bearer ${this.crowdin.$auth.oauth_access_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)
}