iLovePDF
iLovePDF is an online service to work with PDF files completely free and easy to use. Merge PDF, split PDF, compress PDF, office to PDF, and more.
Integrate the iLovePDF API with the Go API
Setup the iLovePDF API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate iLovePDF and Go remarkably fast. Free for developers.
Popular iLovePDF 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.
Process one or more files with the desired tool. See the documentation
Overview of iLovePDF#
The iLovePDF API lets you automate PDF processing tasks like merging, splitting, compressing, and converting PDFs to other formats. iLovePDF's robust functionality can be harnessed in Pipedream workflows, which may include handling PDFs generated from various triggers, processing them as needed, and connecting to other services for storage, data extraction, or further actions based on the transformed PDFs.
Connect iLovePDF#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
ilovepdf: {
type: "app",
app: "ilovepdf",
}
},
async run({steps, $}) {
const data = {
"public_key": `${this.ilovepdf.$auth.public_key}`,
}
return await axios($, {
method: "post",
url: `https://api.ilovepdf.com/v1/auth`,
headers: {
"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)
}