Imejis.io
Make your image creation process effortless, create images using api now.
Integrate the Imejis.io API with the Go API
Setup the Imejis.io API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Imejis.io and Go remarkably fast. Free for developers.
Popular Imejis.io and Go Actions#
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
Overview of Imejis.io#
The Imejis.io API offers a suite of features that allow for the manipulation and management of images. Using Pipedream as a serverless integration platform, you can automate complex image operations, organize image collections, and connect image data with other services and apps. You can create workflows that respond to events, process images in real-time, and seamlessly integrate with numerous apps available in Pipedream's ecosystem.
Connect Imejis.io#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
imejis_io: {
type: "app",
app: "imejis_io",
}
},
async run({steps, $}) {
const data = {
"text": `Hello, world!`,
}
return await axios($, {
method: "post",
url: `https://api.imejis.io/api/designs/{{your_design_id}}`,
headers: {
"dma-api-key": `${this.imejis_io.$auth.api_key}`,
"Content-Type": `application/json`,
},
data,
})
},
})
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)
}