CloudFill

Easily create customized PDFs for your customers and leads! Use simple integrations and easy to use API to create PDF from your templates.

Integrate the CloudFill API with the Go API

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

The CloudFill API specializes in automatic form filling, allowing you to pre-fill web forms with accurate and up-to-date information programmatically. With CloudFill on Pipedream, you can create serverless workflows that trigger form filling operations, handle data extracted from forms, and connect to other apps to streamline complex tasks like data entry, customer onboarding, and lead generation.

Connect CloudFill

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    cloudfill: {
      type: "app",
      app: "cloudfill",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.cloudfill.io/api/meta/pdf/`,
      headers: {
        "X-API-Key": `${this.cloudfill.$auth.api_key}`,
        "accept": `application/json`,
      },
    })
  },
})

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)
}