Tidy
TIDY helps to maintain a clean house. A rental. Your employee's workspace. Your home. All automated through TIDY.
Integrate the Tidy API with the Go API
Setup the Tidy API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate Tidy and Go remarkably fast. Free for developers.
Popular Tidy and Go Actions#
Creates a new address in Tidy. See the documentation(https://help.tidy.com/create-an-address)
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 Tidy#
The Tidy API offers a range of functions tailored for property management, enabling users to automate tasks like booking cleanings, managing properties, and keeping track of services. Integrating the Tidy API into Pipedream workflows opens up possibilities for automating communications, scheduling, and property management tasks by connecting Tidy with hundreds of other apps. This can significantly streamline operations for property managers, cleaning services, and real estate businesses.
Connect Tidy#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
tidy: {
type: "app",
app: "tidy",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.tidy.com/api/v1/addresses`,
headers: {
Authorization: `Bearer ${this.tidy.$auth.api_key}`,
"Accept": `application/json`,
},
})
},
})
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)
}