Kotlin at a Hackathon: Your Ticket to the Top Three
Hackathons are adrenaline, sleepless nights, tons of coffee, and the magic when raw code turns into a working prototype in 48 hours. But if you're still dragging Python or Java to a hackathon, you're missing a trump card. Kotlin is a language that gives you a superpower: write less, do more, and not go crazy from bugs in the early morning.
Why is Kotlin ideal for a hackathon? It's concise, null-safe, supports coroutines (asynchronous without pain) and works everywhere: from Android to backend on Ktor. In this article, I'll share real tips on how to prepare for a Kotlin hackathon and show project examples with code that you can adapt to your idea. Let's go!
Phase 1: Preparation — 80% of Success
A hackathon doesn't start when the theme is announced, but a week before. Here's what you need to do to avoid writing code from scratch.
1. Gather a "Gentleman's Kit" of Libraries
Don't waste time choosing tools. Determine your MVP stack in advance:
- Backend:
Ktor(lightweight, fast, asynchronous) +Exposed(ORM for DB) +H2orPostgreSQL. - Frontend (if needed):
Kotlin/JSorCompose Multiplatform— one language for all screens. - Asynchrony:
Kotlin Coroutines+Flow. - Serialization:
kotlinx.serialization— JSON without pain. - Testing: Built-in
kotlin.test— enough for quick checks.
2. Prepare a Project Template
Create a repository with a basic structure: Ktor setup, database connection, simple CRUD. This will save 2-3 hours on the first day of the hackathon. Example starter file Application.kt:
import io.ktor.server.engine.*import io.ktor.server.netty.*import io.ktor.server.routing.*import io.ktor.server.response.*import io.ktor.server.request.*import io.ktor.http.*
fun main() { embeddedServer(Netty, port = 8080) { routing { get("/") { call.respondText("Hello, Hackathon!", ContentType.Text.Plain) } get("/api/health") { call.respond(mapOf("status" to "ok")) } } }.start(wait = true)}Phase 2: Choosing an Idea — Don't Overcomplicate
At a hackathon, the winners are not the most complex projects, but those that work and solve a specific pain point. Forget about neural networks and blockchain if you don't have a ready-made model. It's better to make a simple but complete product.
Example 1: Telegram Bot for Collecting Feedback in Kotlin
We use Kotlin + TelegramBots (library for bots). The bot collects anonymous feedback from employees and sends it to Google Sheets.
Key features: receiving messages, validation, writing to a table.
import org.telegram.telegrambots.bots.TelegramLongPollingBotimport org.telegram.telegrambots.meta.api.methods.send.SendMessageimport org.telegram.telegrambots.meta.api.objects.Update
class FeedbackBot(token: String) : TelegramLongPollingBot(token) {
override fun onUpdateReceived(update: Update) { val message = update.message.text val chatId = update.message.chatId.toString()
if (message.startsWith("/feedback")) { val feedbackText = message.removePrefix("/feedback ").trim() if (feedbackText.isNotEmpty()) { // Save to DB or send to Google Sheets saveFeedback(feedbackText) sendMessage(chatId, "Thank you! Your feedback has been received.") } else { sendMessage(chatId, "Please write text after /feedback")