Apify

Apify is the place to find, develop, buy and run cloud programs called actors. Use actors to turn any website into an API.

Integrate the Apify API with the Go API

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

The Apify API unleashes the power to automate web scraping, process data, and orchestrate web automation workflows. By utilizing Apify on Pipedream, you can create dynamic serverless workflows to manage tasks like extracting data from websites, running browser automation, and scheduling these jobs to run autonomously. It integrates smoothly with Pipedream's capabilities to trigger actions on various other apps, store the results, and manage complex data flow with minimal setup.

Connect Apify

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