ImageKit.io

Media management, optimization, and delivery solution for a seamless visual experience on websites and apps.

Integrate the ImageKit.io API with the Go API

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

Get File Details with the ImageKit.io API

Get details from a specific file. See the documentation

 
Try it
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
Search Files with the ImageKit.io API

List all the uploaded files and folders in your ImageKit.io media library. See the documentation

 
Try it
Upload Image with the ImageKit.io API

Upload a new image to ImageKit.io. See the documentation

 
Try it

Overview of ImageKit.io

ImageKit.io API lets you manage, optimize, and deliver images dynamically for your web applications. On Pipedream, you can integrate this API to construct serverless workflows that automate your image operations and connect with other services. You can upload images from various sources, apply real-time transformations, and track media assets without managing infrastructure.

Connect ImageKit.io

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    imagekit_io: {
      type: "app",
      app: "imagekit_io",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.imagekit.io/v1/files`,
      auth: {
        username: `${this.imagekit_io.$auth.private_key}`,
        password: ``,
      },
    })
  },
})

Connect Go

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
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)
}