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with YouTube Analytics and Go?
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Popular YouTube Analytics and Go Actions#
Retrieve detailed analytics for a specific video. See the documentation
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
Fetch summary analytics reports for a specified youtube channel. Optional filters include date range and report type. See the documentation
Execute a custom analytics query using specified metrics, dimensions, filters, and date ranges. Requires query parameters to configure. See the documentation
Overview of YouTube Analytics#
The YouTube Analytics API enables you to pull complex, insightful data regarding your YouTube channel's performance, audience demographics, and engagement metrics. It's a goldmine for content creators looking to refine their content strategy based on solid data. Using Pipedream, you can automate the extraction of these analytics, set up real-time alerts, or synchronize this data with other tools for enhanced reporting and decision-making.
Connect YouTube Analytics#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
youtube_analytics_api: {
type: "app",
app: "youtube_analytics_api",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://www.googleapis.com/oauth2/v1/userinfo`,
headers: {
Authorization: `Bearer ${this.youtube_analytics_api.$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)
}Trusted by 1,000,000+ developers from startups to Fortune 500 companies