RAWG Video Games Database
The largest video game database and video game discovery service.
Integrate the RAWG Video Games Database API with the Go API
Setup the RAWG Video Games Database API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate RAWG Video Games Database and Go remarkably fast. Free for developers.
Popular RAWG Video Games Database 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 RAWG Video Games Database#
The RAWG Video Games Database API is a treasure trove for gaming enthusiasts and developers, offering access to a massive collection of video game data. With it, you can pull information such as game titles, ratings, platforms, and release dates. This data can power up apps or websites with rich content or be used to analyze gaming trends. Through Pipedream, you can automate data collection, trigger events based on new or updated game releases, and integrate with other services for notifications or data enrichment.
Connect RAWG Video Games Database#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
rawg_video_games_database: {
type: "app",
app: "rawg_video_games_database",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.rawg.io/api/platforms`,
params: {
key: `${this.rawg_video_games_database.$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#
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)
}