Hive
An all-in-one solution for software and operations to help you manage your D2C brand throughout fulfillment and beyond.
Integrate the Hive API with the Go API
Setup the Hive API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Hive and Go remarkably fast. Free for developers.
Popular Hive 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.
Create an action for given workspace See the documentation
Overview of Hive#
The Hive API allows for robust interaction with Hive's project and team management tools. By leveraging the Hive API within Pipedream, you can automate tasks, sync data across platforms, and create custom workflows that enhance productivity. For instance, you could automate project creation, update task statuses, or sync information to other business tools. Pipedream's serverless platform simplifies integration, enabling you to focus on crafting workflows without worrying about infrastructure.
Connect Hive#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
hive: {
type: "app",
app: "hive",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://app.hive.com/api/v1/users`,
params: {
api_key: `${this.hive.$auth.api_key}`,
user_id: `${this.hive.$auth.user_id}`,
},
})
},
})
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)
}