Google Search Console
Tools and reports help you measure your site's Search traffic
Integrate the Google Search Console API with the Go API
Setup the Google Search Console API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Google Search Console and Go remarkably fast. Free for developers.
Popular Google Search Console and Go Actions#
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 Google Search Console#
The Google Search Console API opens a treasure trove of data and insights about your website’s presence in Google Search results. You can get detailed reports on your site's search traffic, manage and test your site's sitemaps and robots.txt files, and see which queries bring users to your site. On Pipedream, utilize this API to automate checks on site performance, integrate with other tools for deeper analysis, or keep tabs on your SEO strategy's effectiveness.
Connect Google Search Console#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
google_search_console: {
type: "app",
app: "google_search_console",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://www.googleapis.com/webmasters/v3/sites`,
headers: {
Authorization: `Bearer ${this.google_search_console.$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)
}