When we want to transform a Promise value we can use the map and flatMap methods. There are also variants to this methods that will only transform a value when a given predicate is true: mapIf and flatMapIf. We provide a predicate and function to the methods. If the predicate is true the function is invoked, otherwise the function is not invoked and the promised value is returned as is.

In the following example we have two methods that use the mapIf and flatMapIf methods of the Promise class:

Testing a Ratpack application is not difficult. Ratpack has excellent support for writing unit and integration tests. When we create the fixture MainClassApplicationUnderTest we can override the method addImpositions to add mock objects to the application. We can add them using the ImpositionsSpec object. When the application starts with the test fixture the provided mock objects are used instead of the original objects. For a Groovy based Ratpack application we can do the same thing when we create the fixture GroovyRatpackMainApplicationUnderTest.

We start with a simple Java Ratpack application. The application adds an implementation of a NumberService interface to the registry. A handler uses this implementation for rendering some output.

We have several options to define a Ratpack application. We can use a Java syntax to set up the bindings and handlers. Or we can use the very nice Groovy DSL. It turns out we can use both together as well. For example we can define the handlers with the Groovy DSL and the rest of the application definition is written in Java. To combine both we start with the Java configuration and use the bindings and handlers method of the Groovy.Script class to inject the files with the Groovy DSL.

We start with a sample application where we use Java configuration to set up our Ratpack application:

One of the very nice features of Ratpack is the Groovy DSL to define our application. We get a nice DSL to set up the registry, to define handlers and more. Because of clever use of the @DelegateTo annotation we get good code completion in our IDE. We can also add static compilation of our Groovy DSL when we start our Ratpack application. With static compilation the script is type checked at compile time so we get earlier feedback on possible errors in the script. To configure static compilation we must invoke the app method of the Groovy.Script class with the argument true.

We start with a Groovy DSL for an application that serves recipes. Notice the Closure arguments are all typed, so with type checking there are no errors.

Ratpack uses renderers to render output. We can create our own renderer by implementing the Renderer interface. The renderer class needs to implement a render method that has the object we want to render as argument. Alternatively we can add the logic to render a object to the class definition of that object. So instead of having a separate renderer class for a class, we add the render logic to the class itself. To achieve this we must implement the Renderable interface for our class. Ratpack provides a RenderableRenderer in the registry that knows how to render classes that implement the Renderable interface.

In the following example we have a Recipe class that implements the Renderable interface:

Ratpack has parsers to parse a request with a JSON body or a HTML form. We simply use the parse method of Context and Ratpack will check if there is a compliant parser in the registry. If there is a parser for that type available then Ratpack will parse the request and return a Promise with the value. To write a new parser we need to implement the Parser interface. The easiest way to implement this interface is by writing a class that extends ParserSupport. Using the ParserSupport class we can also work with an options object that a user can pass on to the parse method of Context. If we don’t need options we can also extend the NoOptParserSupport class.

Let’s write a custom parser that can parse a request with a hex or base64 encoded value. The parser returns a String object with the decoded value. In our example we also want the user to provide an optional options object of type StringParserOpts which denotes the type of decoding:

In a previous post we learned about Spring Cloud Contract. We saw how we can use contracts to implement the server side of the contract. But Spring Cloud Contract also creates a stub based on the contract. The stub server is implemented with Wiremock and Spring Boot. The server can match incoming requests with the contracts and send back the response as defined in the contract. Let’s write an application that is invoking HTTP requests on the server application we wrote before. In the tests that we write for this client application we use the stub that is generated by Spring Cloud Contract. We know the stub is following the contract of the actual server.

First we create the stub in our server project with the Gradle task verifierStubsJar. The tests in the client application need these stub and will fetch it as dependency from a Maven repository or the local Maven repository. For our example we use the local Maven repository. We add the maven-publish plugin to the server project and run the task publishToMavenLocal.

Spring Cloud Contract is a project that allows to write a contract for a service using a Groovy DSL. In the contract we describe the expected requests and responses for the service. From this contract a stub is generated that can be used by a client application to test the code that invokes the service. Spring Cloud Contract also generates tests based on the contract for the service implementation. Let’s see how we can use the generated tests for the service implementation for a Ratpack application.

Spring Cloud Contract comes with a Gradle plugin. This plugin adds the task generateContractTests that creates tests based on the contract we write. There are also tasks to create the stub for a client application, but here we focus on the server implementation. In the following Gradle build file for our Ratpack application we use the Spring Cloud Contract Gradle plugin. We configure the plugin to use Spock as framework for the generated tests.

When we need to create a URI object in Ratpack we can use the HttpUrlBuilder class. We use several methods to build up a complete URI object in an easy way. This is very useful when we for example use Ratpack’s HttpClient object and we need to pass an URI to do a request.

In the following example specification we see several usages of the HttpUrlBuilder class: