Poof
Empowering millions of digital businesses & creators with payments from crypto to fiat.
Integrate the Poof API with the Go API
Setup the Poof API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Poof and Go remarkably fast. Free for developers.
Popular Poof and Go Triggers#
Emit new events when a payment is made in Poof. See the documentation
Popular Poof and Go Actions#
Creates a new deposit address in Poof. 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.
Overview of Poof#
The Poof API lets you schedule and automate emails and SMS messages, making it a powerful tool for communication-based workflows. With Pipedream, you can connect the Poof API to hundreds of other services to craft custom automations. Trigger events, process data, and design complex interactions without managing a server infrastructure.
Connect Poof#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
poof: {
type: "app",
app: "poof",
}
},
async run({steps, $}) {
const data = {
"crypto": `bitcoin`,
}
return await axios($, {
method: "post",
url: `https://www.poof.io/api/v2/balance`,
headers: {
"Authorization": `${this.poof.$auth.api_key}`,
"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)
}