with Interzoid and Go?
Generate a Match Report using a dataset table or file (CSV/TSV/Excel). 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.
Retrieve a match score (likelihood of matching) between two individual names on a scale of 0-100. See the documentation
Retrieve a match score (likelihood of matching) from 0-100 between two organization names. See the documentation
The Interzoid API offers a plethora of data-driven APIs that enable you to enrich, standardize, and deduplicate data across various fields such as demographics, financials, and text. With these capabilities, you can enhance data quality, drive better analytics, and create more intelligent workflows and applications. In Pipedream, you can integrate these APIs into serverless workflows, triggering actions based on various events, manipulating and routing data to other apps, services, or data stores with ease.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
interzoid: {
type: "app",
app: "interzoid",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.interzoid.com/getremainingcredits`,
params: {
license: `${this.interzoid.$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)
}