Integrate the SoftLedger API with the Go API

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

Popular SoftLedger and Go Actions#

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 SoftLedger#

SoftLedger is a powerful API that enables you to automate accounting and financial tasks by integrating with your existing financial stack. By leveraging SoftLedger API on Pipedream, you can create custom workflows that streamline financial reporting, manage inventory, automate ledger entries, and sync financial data across applications. Pipedream's serverless platform allows you to connect the SoftLedger API with hundreds of other apps to trigger actions, process data, and automate repetitive tasks without writing complex code.

Connect SoftLedger#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    softledger: {
      type: "app",
      app: "softledger",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.softledger.com/api/locations/me`,
      headers: {
        Authorization: `Bearer ${this.softledger.$auth.oauth_access_token}`,
      },
    })
  },
})

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)
}