Integrate the Capsule API with the Go API

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

Popular Capsule 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 Capsule#

The Capsule API provides access to a treasure trove of customer relationship management (CRM) functions. Through Pipedream's serverless platform, it becomes fantastically simple to automate interactions with your Capsule CRM data. Envision syncing contacts, managing cases, tracking sales opportunities, or even automating follow-up emails based on customer behavior. The workflows created can be both time-saving and insightful, providing not just automation but also analytics on customer engagements.

Connect Capsule#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    capsule: {
      type: "app",
      app: "capsule",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.capsulecrm.com/api/v2/users/current`,
      headers: {
        Authorization: `Bearer ${this.capsule.$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)
}