SEMrush

Get measurable results from online marketing. Do SEO, content marketing, competitor research, PPC and social media marketing from just one platform.

Integrate the SEMrush API with the Go API

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

The SEMrush API offers a suite of tools for SEO, content marketing, competitor research, PPC and social media marketing analysis. With Pipedream's capabilities, you can automate data extraction for SEO audits, track keyword rankings, and glean insights from your competitors' online strategies. By utilizing the SEMrush API on Pipedream, you can create workflows that trigger actions in other apps, generate reports, and streamline your marketing efforts.

Connect SEMrush

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    semrush: {
      type: "app",
      app: "semrush",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `http://www.semrush.com/users/countapiunits.html`,
      params: {
        key: `${this.semrush.$auth.api_key}`,
      },
    })
  },
})

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)
}