with DEAR Systems and Go?
Emit new event when a purchase order is created and authorized
Emit new event when a sale order is created and authorized
Emit new event when a sale quote is created and authorized
Emit new event when the available stock level changes. See the documentation
Emit new event when a customer is updated. 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.
DEAR Systems offers an API that provides programmatic access to its inventory management platform, allowing for seamless integration with other apps for automating various business processes. Leveraging this API within Pipedream, you can create custom workflows to synchronize inventory levels, manage sales and purchase orders, and automate financial reporting among other tasks. By connecting DEAR Systems to Pipedream’s vast array of supported apps, you can achieve a high degree of automation, reducing manual entry and data errors, and gaining insights from real-time data processing.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
dear: {
type: "app",
app: "dear",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://inventory.dearsystems.com/ExternalApi/v2/me`,
headers: {
"api-auth-accountid": `${this.dear.$auth.account_id}`,
"api-auth-applicationkey": `${this.dear.$auth.application_key}`,
},
})
},
})
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.
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)
}