Airparser
Revolutionize data extraction with the GPT-powered document parser.
Integrate the Airparser API with the Go API
Setup the Airparser API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Airparser and Go remarkably fast. Free for developers.
Popular Airparser and Go Triggers#
Emit new event when a document is parsed. See the documentation
Popular Airparser and Go Actions#
Extracts structured data based on a user-predefined extraction schema. 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.
Uploads a document into the inbox for data extraction. See the documentation
Overview of Airparser#
The Airparser API simplifies the process of extracting data from emails, such as order confirmations, shipping notifications, or any structured email content. By transforming emails into structured data, it enables seamless integration of email data into various workflows. On Pipedream, you can leverage this API to create automations that act on the parsed data—like updating databases, triggering notifications, or integrating with other apps and services.
Connect Airparser#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
airparser: {
type: "app",
app: "airparser",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.airparser.com/inboxes/`,
headers: {
"X-API-Key": `${this.airparser.$auth.api_key}`,
},
})
},
})
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)
}