Autocomplete, Verify, Validate, and Standardize addresses to local postal standards for better deliverability, up-to-date records, and eliminating return mail.
Break an address apart into its components. 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.
Verify, standardize, and correct an address written on a single line. Ensure that you add the ISO 2-letter country code to the end of the line for best results. See the documentation.
The PostGrid Verify API offers a precise method to validate and standardize postal addresses. By integrating with this API on Pipedream, you can automate the process of scrubbing address data within your apps, ensuring accuracy and deliverability. This could be critical for businesses that depend on reliable mailing operations, CRM data accuracy, or e-commerce checkout processes. Using Pipedream, you can create serverless workflows that respond to events, verify addresses on-the-fly, and connect with countless other services for enhanced data management.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
postgrid_verify: {
type: "app",
app: "postgrid_verify",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.postgrid.com/v1/addver`,
headers: {
"x-api-key": `${this.postgrid_verify.$auth.api_key}`,
},
})
},
})
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)
}