1. Overview
Ratpack is a set of JVM based libraries built for modern days high-performance real-time applications. It’s built on top of embedded Netty event-driven networking engine and is fully compliant with the reactive design pattern.
In this article, we’ll learn how to use Ratpack and we’ll build a small application using it.
2. Why Ratpack?
The main advantages of Ratpack:
- it’s very lightweight, fast and scalable
- it consumes less memory than other frameworks such as DropWizard; an interesting benchmark comparison result can be found here
- since it’s built on top of Netty, Ratpack is totally event-driven and non-blocking in nature
- it has support for Guice dependency management
- much like Spring Boot, Ratpack has its own testing libraries to quickly setup test-cases
3. Creating an Application
To understand how Ratpack works, let’s start by creating a small application with it.
3.1. Maven Dependencies
First, let’s add the following dependencies into our pom.xml:
<dependency>
<groupId>io.ratpack</groupId>
<artifactId>ratpack-core</artifactId>
<version>1.4.5</version>
</dependency>
<dependency>
<groupId>io.ratpack</groupId>
<artifactId>ratpack-test</artifactId>
<version>1.4.5</version>
</dependency>
You can check the latest version on Maven Central.
Note that although we are using Maven as our build system, as per Ratpack recommendation, it’s better to use Gradle as a build tool since Ratpack has first-class Gradle support provided via the Ratpack’s Gradle plugin.
We can use the following build Gradle script:
buildscript {
repositories {
jcenter()
}
dependencies {
classpath "io.ratpack:ratpack-gradle:1.4.5"
}
}
apply plugin: "io.ratpack.ratpack-java"
repositories {
jcenter()
}
dependencies {
testCompile 'junit:junit:4.11'
runtime "org.slf4j:slf4j-simple:1.7.21"
}
test {
testLogging {
events 'started', 'passed'
}
}
3.2. Building the Application
Once our build management is configured, we need to create a class to start the embedded Netty server and build a simple context to handle the default requests:
public class Application {
public static void main(String[] args) throws Exception {
RatpackServer.start(server -> server.handlers(chain -> chain
.get(ctx -> ctx.render("Welcome to Baeldung ratpack!!!"))));
}
}
As we can see, by using RatpackServer we can now start the server (default port 5050). The handlers() method takes a function that receives a Chain object, which maps all the respective incoming requests. This “Handler Chain API” is used for building the response handling strategy.
If we run this code snippet and hit the browser at http://localhost:5050, “Welcome to Baeldung ratpack!!!” should be displayed.
Similarly, we can map an HTTP POST request.
3.3. Handling URL Path Parameters
In the next example, we need to capture some URL path param in our application. In Ratpack we use PathTokens to capture them:
RatpackServer.start(server -> server
.handlers(chain -> chain
.get(":name", ctx -> ctx.render("Hello "
+ ctx.getPathTokens().get("name") + " !!!"))));
Here, we’re mapping the name URL param. Whenever a request like http://localhost:5050/John would come, the response will be “Hello John !!!”.
3.4. Request/Response Header Modification With/Without Filter
Sometimes, we need to modify the inline HTTP response header based on our need. Ratpack has MutableHeaders to customize outgoing responses.
For example, we need to alter following headers in the response: Access-Control-Allow-Origin, Accept-Language, and Accept-Charset:
RatpackServer.start(server -> server.handlers(chain -> chain.all(ctx -> {
MutableHeaders headers = ctx.getResponse().getHeaders();
headers.set("Access-Control-Allow-Origin", "*");
headers.set("Accept-Language", "en-us");
headers.set("Accept-Charset", "UTF-8");
ctx.next();
}).get(":name", ctx -> ctx
.render("Hello " + ctx.getPathTokens().get("name") + "!!!"))));
By using MutableHeaders we set are setting the three headers and pushing them in the Chain.
In the same way, we can check the incoming request headers too:
ctx.getRequest().getHeaders().get("//TODO")
The same can be achieved by creating a filter. Ratpack has a Handler interface*,* which can be implemented to create a filter. It has only one method handle(), which takes the current Context as a parameter:
public class RequestValidatorFilter implements Handler {
@Override
public void handle(Context ctx) throws Exception {
MutableHeaders headers = ctx.getResponse().getHeaders();
headers.set("Access-Control-Allow-Origin", "*");
ctx.next();
}
}
We can use this filter in the following way:
RatpackServer.start(
server -> server.handlers(chain -> chain
.all(new RequestValidatorFilter())
.get(ctx -> ctx.render("Welcome to baeldung ratpack!!!"))));
}
3.5. JSON Parser
Ratpack internally uses faster-jackson for JSON parsing. We can use Jackson module to parse any object to JSON.
Let’s create a simple POJO class which will be used for parsing:
public class Employee {
private Long id;
private String title;
private String name;
// getters and setters
}
Here, we have created one simple POJO class named Employee, which has three parameters: id, title, and name. Now we will use this Employee object to convert into JSON and return the same when certain URL is hit:
List<Employee> employees = new ArrayList<Employee>();
employees.add(new Employee(1L, "Mr", "John Doe"));
employees.add(new Employee(2L, "Mr", "White Snow"));
RatpackServer.start(
server -> server.handlers(chain -> chain
.get("data/employees",
ctx -> ctx.render(Jackson.json(employees)))));
As we can see, we are manually adding two Employee objects into a list and parsing them as JSON using Jackson module. As soon as the /data/employees URL is hit, the JSON object will be returned.
Point to note here is that we are not using ObjectMapper at all since Ratpack’s Jackson module will do the needful on the fly.
3.6. In-Memory Database
Ratpack has the first class support for in-memory databases. It uses HikariCP for JDBC connection pooling. In order to use it, we need to add Ratpack’s HikariCP module dependency in the pom.xml:
<dependency>
<groupId>io.ratpack</groupId>
<artifactId>ratpack-hikari</artifactId>
<version>1.4.5</version>
</dependency>
If we are using Gradle, the same needs to be added in the Gradle build file:
compile ratpack.dependency('hikari')
Now, we need to create an SQL file with table DDL statements so that the tables are created as soon as the server is up and running. We’ll create the DDL.sql file in the src/main/resources directory and add some DDL statements into it.
Since we’re using H2 database, we have to add dependencies for that too.
Now, by using HikariModule, we can initialize the database at the runtime:
RatpackServer.start(
server -> server.registry(Guice.registry(bindings ->
bindings.module(HikariModule.class, config -> {
config.setDataSourceClassName("org.h2.jdbcx.JdbcDataSource");
config.addDataSourceProperty("URL",
"jdbc:h2:mem:baeldung;INIT=RUNSCRIPT FROM 'classpath:/DDL.sql'");
}))).handlers(...));
4. Testing
As mentioned earlier, Ratpack has first-class support for jUnit test cases. By using MainClassApplicationUnderTest we can easily create test cases and test the endpoints:
@RunWith(JUnit4.class)
public class ApplicationTest {
MainClassApplicationUnderTest appUnderTest
= new MainClassApplicationUnderTest(Application.class);
@Test
public void givenDefaultUrl_getStaticText() {
assertEquals("Welcome to baeldung ratpack!!!",
appUnderTest.getHttpClient().getText("/"));
}
@Test
public void givenDynamicUrl_getDynamicText() {
assertEquals("Hello dummybot!!!",
appUnderTest.getHttpClient().getText("/dummybot"));
}
@Test
public void givenUrl_getListOfEmployee()
throws JsonProcessingException {
List<Employee> employees = new ArrayList<Employee>();
ObjectMapper mapper = new ObjectMapper();
employees.add(new Employee(1L, "Mr", "John Doe"));
employees.add(new Employee(2L, "Mr", "White Snow"));
assertEquals(mapper.writeValueAsString(employees),
appUnderTest.getHttpClient().getText("/data/employees"));
}
@After
public void shutdown() {
appUnderTest.close();
}
}
Please note that we need to manually terminate the running MainClassApplicationUnderTest instance by calling the close() method as it may unnecessarily block JVM resources. That’s why we have used @After annotation to forcefully terminate the instance once the test case executed.
5. Conclusion
In this article, we saw the simplicity of using Ratpack.
As always, the full source code is available over on GitHub.