Create, convert, transform, OCR PDFs and more.
Extracts text and table element information from a PDF document and returns a JSON file along with table data in XLSX format within a .zip file saved to the /tmp
directory. See the documentation
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
Extracts text element information from a PDF document and returns a JSON file within a .zip file saved to the /tmp
directory. See the documentation
The Adobe PDF Services API provides a robust set of tools for manipulating and managing PDF files. With this API, you can create, convert, combine, export, and manipulate PDFs directly in Pipedream. The Pipedream platform enables you to build automated workflows that can interact with this API to streamline document-centric processes, such as generating reports, archiving files, or extracting data from PDFs into other formats.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
adobe_pdf_services: {
type: "app",
app: "adobe_pdf_services",
}
},
async run({steps, $}) {
const data = {
"mediaType": `application/pdf`,
}
return await axios($, {
method: "post",
url: `https://pdf-services.adobe.io/assets`,
headers: {
Authorization: `Bearer ${this.adobe_pdf_services.$auth.oauth_access_token}`,
"x-api-key": `${this.adobe_pdf_services.$auth.client_id}`,
"Content-Type": `application/json`,
},
data,
})
},
})
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.
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)
}