DocRaptor
The best and easiest HTML-to-PDF API
Integrate the DocRaptor API with the Go API
Setup the DocRaptor API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate DocRaptor and Go remarkably fast. Free for developers.
Popular DocRaptor 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 DocRaptor#
DocRaptor is an API that converts HTML to PDF or XLS(X). Using DocRaptor with Pipedream allows you to automate document generation within your custom workflows. With Pipedream's serverless platform, you can trigger document creation from a multitude of events, process the data, and integrate it with countless apps to create dynamic, on-demand documents. Whether you need to generate invoices, reports, or any other documents, you can set up a pipeline that does the heavy lifting for you.
Connect DocRaptor#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
docraptor: {
type: "app",
app: "docraptor",
}
},
async run({steps, $}) {
const data = {
"type": `pdf`,
"document_content": `<html><body>Hello World!</body></html>`,
}
return await axios($, {
method: "post",
url: `https://api.docraptor.com/docs`,
auth: {
username: `${this.docraptor.$auth.api_key}`,
password: ``,
},
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)
}