File converter service
Emit new event when a CloudConvert job has failed. See the documentation
Emit new event when a CloudConvert job has been completed. See the documentation
Emit new event when a new job has been created. See the documentation
Converts an input file to a specified output format using CloudConvert. 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.
Creates an archive in a specified format. See the documentation
Creates a task to import a file from a URL. See the documentation
Combines multiple input files into a single PDF file and create an export URL with a job. See the documentation
The Cloud Convert API offers a robust solution for file conversion, supporting a vast array of file formats. With Pipedream, you can harness this versatility to create automated workflows that trigger file conversions, process the resulting files, and integrate with other services. By combining Cloud Convert with Pipedream's connectivity to hundreds of apps, you can craft custom automation that saves time and removes the friction from multi-format file management tasks.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
cloud_convert: {
type: "app",
app: "cloud_convert",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.cloudconvert.com/v2/users/me`,
headers: {
Authorization: `Bearer ${this.cloud_convert.$auth.oauth_access_token}`,
},
})
},
})
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)
}