pretix

Ticketing software that cares about your event—all the way.

Integrate the pretix API with the Go API

Setup the pretix API trigger to run a workflow which integrates with the Go API. Pipedream's integration platform allows you to integrate pretix and Go remarkably fast. Free for developers.

Get Order Details with the pretix API

Returns information on one order, identified by its order code. See the documentation

 
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Run Go Code with the Go API

Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.

 
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Update Event with the pretix API

Updates a specific event. See the documentation

 
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Overview of pretix

The pretix API enables seamless integration of your event management tasks by automating ticket sales, attendee management, and event analytics. With Pipedream's capabilities, you can build custom workflows that respond to various pretix events, synchronize attendee data with other services, or analyze sales patterns for actionable insights.

Connect pretix

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    pretix: {
      type: "app",
      app: "pretix",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://pretix.eu/api/v1/me`,
      headers: {
        Authorization: `Bearer ${this.pretix.$auth.oauth_access_token}`,
      },
    })
  },
})

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

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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)
}