Examples/Storm Movies · Kotlin + Ktor

Storm Movies · Kotlin + Ktor

A server-rendered movie browser on Ktor 3 with the Storm plugin: automatic repository registration, Koin wiring via stormModule(), coroutine-native transactions, kotlinx.serialization for the JSON APIs, and Playwright-driven interface tests.

KotlinKtor 3KoinPostgreSQL
$git clone https://github.com/storm-orm/storm-example-kotlin-ktor.git
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An example movie browser built with Storm ORM on Ktor and Kotlin. It imports the public IMDB dataset into PostgreSQL and serves a server-rendered web app (Thymeleaf + a little vanilla JS) for browsing movies, people, genres, ratings, and a watchlist.

The project exists to show what idiomatic Storm looks like in a real Ktor application: immutable data-class entities, metamodel-based queries, coroutine-native transactions, and schema validation. No JPA, no proxies, no persistence context.

Stack

  • Kotlin 2.2 / Java 21, Ktor 3.1 (Netty, Thymeleaf, ContentNegotiation)
  • Storm ORM (storm-ktor, storm-ktor-koin) with the KSP metamodel generator and the Storm compiler plugin
  • Koin for dependency injection
  • PostgreSQL 17 (Docker Compose) with Flyway migrations, run explicitly at startup
  • kotlinx.serialization for JSON APIs and cache values; Jackson for parsing external APIs
  • JUnit 5 + storm-test on H2 for repository tests, Playwright for interface tests

Running the application

Prerequisites: JDK 21 and Docker.

# 1. Start PostgreSQL
docker compose up -d

# 2. Start the application
./gradlew run

# 3. Open the app
open http://localhost:8080

On first startup the app runs the Flyway migration and imports the IMDB dataset: movies with at least 1,000 votes (configurable via imdb.import.minimumVoteCount), plus their genres, cast, crew, and ratings. The dataset files (~1.2 GB) are downloaded once and cached in ./data, then streamed through Storm's suspending batch inserts, so expect the first startup to take a few minutes. The import is skipped entirely on subsequent startups once movie data is present.

To start over with an empty database:

docker compose down -v

Movie posters, person photos, and plot summaries are fetched at runtime from the IMDB suggestion API and the Wikipedia REST API, so the app looks best with internet access.

Project layout

src/main/kotlin/st/orm/demo/imdb/
├── Application.kt   Ktor module: plugin setup (Storm with the Flyway
│                    migration hook, serialization, Thymeleaf)
├── Koin.kt          Koin wiring: Storm's stormModule() exposes the
│                    auto-registered repositories, singleOf wires the services
├── model/          Storm entities (@PK, @FK) and projections
├── repository/     EntityRepository interfaces with QueryBuilder queries
├── service/        Business logic in suspend `transaction { }` blocks,
│                   plus the streaming IMDB importer
├── web/            configureRouting plus the page and REST routes (/api/**)
└── serialization/  kotlinx.serialization support: custom serializers and
                    the JSON-serialized cache
src/main/resources/
├── db/migration/   Flyway schema (V1__create_schema.sql)
├── templates/      Thymeleaf views
└── static/         CSS, JS, images

What to look at

Each part of the app demonstrates a Storm feature:

  • Entities (model/): immutable data classes with @PK, @FK, @UK, and composite keys (MovieGenre, Principal). MovieView is a database-view-backed projection; MovieSummary / PersonSummary select a subset of columns.
  • Repositories (repository/): EntityRepository interfaces with default methods using the type-safe QueryBuilder and generated metamodel (Movie_.startYear, Principal_.person). Aggregations return plain data classes; computed expressions use SQL template lambdas with metamodel references.
  • Transactions (service/): Storm's coroutine-native suspend transaction { } blocks at the service level, called directly from Ktor's suspend route handlers, with no runBlocking bridge in the request path. Storm manages transactions on the DataSource directly, with no framework transaction manager involved.
  • Streaming import (service/ImdbDataImporter.kt): Flow-based pipeline that parses TSV rows into entities and hands them to Storm's suspending batch insert, one pass per file, without materializing entity lists. It runs once at application startup, blocking until finished.
  • Schema validation: on by default. The Storm plugin verifies every entity against the live database schema at startup and fails fast on any mismatch; the Flyway migration hook runs first, so validation always sees the migrated schema. EntitySchemaValidationTest does the same in the test suite.
  • Serialization (serialization/, web/ApiModels.kt): Storm entities serialized with kotlinx.serialization for the REST endpoints, and a cache that stores values as serialized JSON to prove entities survive the round-trip (KotlinxSerializedCache, used explicitly by StatisticsService).
  • Startup wiring (Application.kt, Koin.kt): one install(Storm) plugin with the Flyway migration hook, and Koin for dependency injection: stormModule() (from storm-ktor-koin) exposes the ORMTemplate and every auto-registered repository by type, so services are wired with singleOf(::HomeService), with no manual lookups.

Testing

./gradlew test

Repository tests run on an in-memory H2 database via @StormTest, so no Docker is required. Tests receive an ORMTemplate and a SqlCapture as parameters, so they can assert on the SQL Storm generates.

The Playwright interface tests run against a live application:

./gradlew installPlaywrightBrowsers   # once
./gradlew run                         # in one terminal
./gradlew e2eTest                     # in another

Configuration

Everything lives in src/main/resources/application.conf. The defaults match the Compose file (database imdb, user/password storm on localhost:5432). Import behavior is tunable under imdb.import (cache directory, minimum vote count, dataset base URL).

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