HUB Planner
A Modern and Smart Resource Management, Planning & Scheduling tool with Time Sheets and Powerful Reporting. Ideal for Managing Global Teams of Resources.
Integrate the HUB Planner API with the Go API
Setup the HUB Planner API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate HUB Planner and Go remarkably fast. Free for developers.
Popular HUB Planner 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 HUB Planner#
The HUB Planner API is a toolset for managing resources, projects, and bookings in a visual and interactive way. By using the API with Pipedream, you can automate complex workflows, sync data across multiple platforms, and create custom integrations to streamline operations. From scheduling resources to analyzing project data, the opportunities are vast for enhancing project management efficiency.
Connect HUB Planner#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
hub_planner: {
type: "app",
app: "hub_planner",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.hubplanner.com/v1/project`,
headers: {
"Authorization": `${this.hub_planner.$auth.api_key}`,
"Accept": `application/json`,
"Content-Type": `application/json`,
},
})
},
})
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)
}