Integrate the Algorithmia API with the Go API

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

Popular Algorithmia 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 Algorithmia#

The Algorithmia API provides access to a myriad of algorithms in various categories like machine learning, data analysis, and natural language processing. By utilizing this API on Pipedream, you can automate complex tasks that require advanced computations, such as sentiment analysis, image processing, or predictive modeling, without the need to develop and maintain the underlying algorithms yourself. Pipedream's serverless platform allows you to seamlessly integrate these capabilities with other services to create powerful data processing pipelines.

Connect Algorithmia#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    algorithmia: {
      type: "app",
      app: "algorithmia",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      method: "post",
      url: `https://api.algorithmia.com/v1/algo/demo/Hello/`,
      headers: {
        "Authorization": `Simple ${this.algorithmia.$auth.YOUR_API_KEY}`,
      },
    })
  },
})

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)
}