Apiary

Platform for API Design, Development & Documentation

Integrate the Apiary API with the Go API

Setup the Apiary API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Apiary 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 Apiary

The Apiary API, part of the Foursquare suite of applications, opens a treasure trove of location-based data and functionality. It's a powerful tool for developers aiming to enrich their apps with detailed information about venues, user check-ins, and location-based recommendations. From creating personalized travel guides to enhancing event management systems with nearby point of interest (POI) suggestions, Apiary's robust set of endpoints can be leveraged to tailor user experiences based on their real-world surroundings.

Connect Apiary

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

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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)
}