WhosOnLocation
Track and manage onsite employees, visitors, and contractors with touchless workplace sign-in, desk booking, wellness checks, and more.
Integrate the WhosOnLocation API with the Go API
Setup the WhosOnLocation API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate WhosOnLocation and Go remarkably fast. Free for developers.
Popular WhosOnLocation 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 WhosOnLocation#
The WhosOnLocation API allows you to manage and track people's presence in various locations, such as office buildings, worksites, and campuses. In Pipedream, you can leverage this API to create automations that streamline visitor management, employee attendance, and emergency roll-calls. By crafting serverless workflows, you can respond to events in real-time, synchronize data with other systems, and enhance security and compliance processes.
Connect WhosOnLocation#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
whosonlocation: {
type: "app",
app: "whosonlocation",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.whosonlocation.com/v1/staff`,
auth: {
username: `${this.whosonlocation.$auth.api_key}`,
password: ``,
},
})
},
})
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)
}