Truss

Shockingly simple client requests. Truss is the easiest way for CPAs, EAs and Accountants to securely request and organize client documents.

Integrate the Truss API with the Go API

Setup the Truss API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Truss and Go remarkably fast. Free for developers.

Run Go Code with the Go API

Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.

 
Try it

Overview of Truss

The Truss API enables automation and integration of project management functionalities. With Truss, you can manage tasks, projects, and resources within your organization by automating workflows and connecting to other services. By leveraging Pipedream's capabilities, you can create complex automations that respond to events in Truss, manipulate data, and trigger actions in other apps, all without the need to manage infrastructure.

Connect Truss

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    truss: {
      type: "app",
      app: "truss",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://app2.gettruss.io/api/v1/users`,
      headers: {
        Authorization: `Bearer ${this.truss.$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

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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)
}