Showing posts with label rest assured. Show all posts
Showing posts with label rest assured. Show all posts

Tuesday, November 6, 2018

Building Enterprise Java applications, the Spring way

I think it is fair to say that Java EE has gained pretty bad reputation among Java developers. Despite the fact that it has certainly improved on all fronts over the years, even changed home to Eclipse Foundation to become Jakarta EE, its bitter taste is still quite strong. On the other side we have Spring Framework (or to reflect the reality better, a full-fledged Spring Platform): brilliant, lightweight, fast, innovative and hyper-productive Java EE replacement. So why to bother with Java EE?

We are going to answer this question by showing how easy it is to build modern Java applications using most of Java EE specs. And the key ingredient to succeed here is Eclipse Microprofile: enterprise Java in the age of microservices.

The application we are going to build is RESTful web API to manage people, as simple as that. The standard way to build RESTful web services in Java is by using JAX-RS 2.1 (JSR-370). Consequently, CDI 2.0 (JSR-365) is going to take care of dependency injection whereas JPA 2.0 (JSR-317) is going to cover the data access layer. And certainly, Bean Validation 2.0 (JSR-380) is helping us to deal with input verification.

The only non-Java EE specification we would be relying on is OpenAPI v3.0 which helps to provide the usable description of our RESTful web APIs. With that, let us get started with the PersonEntity domain model (omitting getters and setters as not very relevant details):

@Entity
@Table(name = "people")
public class PersonEntity {
    @Id @Column(length = 256) 
    private String email;

    @Column(nullable = false, length = 256, name = "first_name")
    private String firstName;

    @Column(nullable = false, length = 256, name = "last_name")
    private String lastName;

    @Version
    private Long version;
}

It just has the absolute minimum set of properties. The JPA repository is pretty straightforward and implements typical set of CRUD methods.

@ApplicationScoped
@EntityManagerConfig(qualifier = PeopleDb.class)
public class PeopleJpaRepository implements PeopleRepository {
    @Inject @PeopleDb private EntityManager em;

    @Override
    @Transactional(readOnly = true)
    public Optional<PersonEntity> findByEmail(String email) {
        final CriteriaBuilder cb = em.getCriteriaBuilder();
    
        final CriteriaQuery<PersonEntity> query = cb.createQuery(PersonEntity.class);
        final Root<PersonEntity> root = query.from(PersonEntity.class);
        query.where(cb.equal(root.get(PersonEntity_.email), email));
        
        try {
            final PersonEntity entity = em.createQuery(query).getSingleResult();
            return Optional.of(entity);
        } catch (final NoResultException ex) {
            return Optional.empty();
        }
    }

    @Override
    @Transactional
    public PersonEntity saveOrUpdate(String email, String firstName, String lastName) {
        final PersonEntity entity = new PersonEntity(email, firstName, lastName);
        em.persist(entity);
        return entity;
    }

    @Override
    @Transactional(readOnly = true)
    public Collection<PersonEntity> findAll() {
        final CriteriaBuilder cb = em.getCriteriaBuilder();
        final CriteriaQuery<PersonEntity> query = cb.createQuery(PersonEntity.class);
        query.from(PersonEntity.class);
        return em.createQuery(query).getResultList();
    }

    @Override
    @Transactional
    public Optional<PersonEntity> deleteByEmail(String email) {
        return findByEmail(email)
            .map(entity -> {
                em.remove(entity);
                return entity;
            });
    }
}

The transaction management (namely, the @Transactional annotation) needs some explanation. In the typical Java EE application, the container runtime is responsible for managing the transactions. Since we don't want to onboard the application container but stay lean, we could have used EntityManager to start / commit / rollback transactions. It would certainly work out but pollute the code with the boilerplate. Arguably, the better option is to use Apache DeltaSpike CDI extensions for declarative transaction management (this is where @Transactional and @EntityManagerConfig annotations are coming from). The snippet below illustrates how it is being integrated.

@ApplicationScoped
public class PersistenceConfig {
    @PersistenceUnit(unitName = "peopledb")
    private EntityManagerFactory entityManagerFactory;

    @Produces @PeopleDb @TransactionScoped
    public EntityManager create() {
        return this.entityManagerFactory.createEntityManager();
    }

    public void dispose(@Disposes @PeopleDb EntityManager entityManager) {
        if (entityManager.isOpen()) {
            entityManager.close();
        }
    }
}

Awesome, the hardest part is already behind! The Person data transfer object and the service layer are coming next.

public class Person {
    @NotNull private String email;
    @NotNull private String firstName;
    @NotNull private String lastName;
}

Honestly, for the sake of keeping the example application as small as possible we could skip the service layer altogether and go to the repository directly. But this is, in general, not a very good practice so let us introduce PeopleServiceImpl anyway.

@ApplicationScoped
public class PeopleServiceImpl implements PeopleService {
    @Inject private PeopleRepository repository;

    @Override
    public Optional<Person> findByEmail(String email) {
        return repository
            .findByEmail(email)
            .map(this::toPerson);
    }

    @Override
    public Person add(Person person) {
        return toPerson(repository.saveOrUpdate(person.getEmail(), person.getFirstName(), person.getLastName()));
    }

    @Override
    public Collection<Person> getAll() {
        return repository
            .findAll()
            .stream()
            .map(this::toPerson)
            .collect(Collectors.toList());
    }

    @Override
    public Optional<Person> remove(String email) {
        return repository
            .deleteByEmail(email)
            .map(this::toPerson);
    }
    
    private Person toPerson(PersonEntity entity) {
        return new Person(entity.getEmail(), entity.getFirstName(), entity.getLastName());
    }
}

The only part left is the definition of the JAX-RS application and resources.

@Dependent
@ApplicationPath("api")
@OpenAPIDefinition(
    info = @Info(
        title = "People Management Web APIs", 
        version = "1.0.0", 
        license = @License(
            name = "Apache License", 
            url = "https://www.apache.org/licenses/LICENSE-2.0"
        )
    )
)
public class PeopleApplication extends Application {
}

Not much to say, as simple as it could possibly be. The JAX-RS resource implementation is a bit more interesting though (the OpenAPI annotations are taking most of the place).

@ApplicationScoped
@Path( "/people" ) 
@Tag(name = "people")
public class PeopleResource {
    @Inject private PeopleService service;
    
    @Produces(MediaType.APPLICATION_JSON)
    @GET
    @Operation(
        description = "List all people", 
        responses = {
            @ApiResponse(
                content = @Content(array = @ArraySchema(schema = @Schema(implementation = Person.class))),
                responseCode = "200"
            )
        }
    )
    public Collection<Person> getPeople() {
        return service.getAll();
    }

    @Produces(MediaType.APPLICATION_JSON)
    @Path("/{email}")
    @GET
    @Operation(
        description = "Find person by e-mail", 
        responses = {
            @ApiResponse(
                content = @Content(schema = @Schema(implementation = Person.class)), 
                responseCode = "200"
            ),
            @ApiResponse(
                responseCode = "404", 
                description = "Person with such e-mail doesn't exists"
            )
        }
    )
    public Person findPerson(@Parameter(description = "E-Mail address to lookup for", required = true) @PathParam("email") final String email) {
        return service
            .findByEmail(email)
            .orElseThrow(() -> new NotFoundException("Person with such e-mail doesn't exists"));
    }

    @Consumes(MediaType.APPLICATION_JSON)
    @Produces(MediaType.APPLICATION_JSON)
    @POST
    @Operation(
        description = "Create new person",
        requestBody = @RequestBody(
            content = @Content(schema = @Schema(implementation = Person.class)),
        ), 
        responses = {
            @ApiResponse(
                 content = @Content(schema = @Schema(implementation = Person.class)),
                 headers = @Header(name = "Location"),
                 responseCode = "201"
            ),
            @ApiResponse(
                responseCode = "409", 
                description = "Person with such e-mail already exists"
            )
        }
    )
    public Response addPerson(@Context final UriInfo uriInfo,
            @Parameter(description = "Person", required = true) @Valid Person payload) {

        final Person person = service.add(payload);
        return Response
             .created(uriInfo.getRequestUriBuilder().path(person.getEmail()).build())
             .entity(person)
             .build();
    }
    
    @Path("/{email}")
    @DELETE
    @Operation(
        description = "Delete existing person",
        responses = {
            @ApiResponse(
                responseCode = "204",
                description = "Person has been deleted"
            ),
            @ApiResponse(
                responseCode = "404", 
                description = "Person with such e-mail doesn't exists"
            )
        }
    )
    public Response deletePerson(@Parameter(description = "E-Mail address to lookup for", required = true ) @PathParam("email") final String email) {
        return service
            .remove(email)
            .map(r -> Response.noContent().build())
            .orElseThrow(() -> new NotFoundException("Person with such e-mail doesn't exists"));
    }
}

And with that, we are done! But how could we assemble and wire all these pieces together? Here is the time for Microprofile to enter the stage. There are many implementations to chose from, the one we are going to use in this post is Project Hammock. The only thing we have to do is to specify the CDI 2.0, JAX-RS 2.1 and JPA 2.0 implementations we would like to use, which translates to Weld, Apache CXF, and OpenJPA respectively (expressed through the Project Hammock dependencies). Let us take a look on the Apache Maven pom.xml file.

<properties>
    <deltaspike.version>1.8.1</deltaspike.version>
    <hammock.version>2.1</hammock.version>
</properties>

<dependencies>
    <dependency>
        <groupId>org.apache.deltaspike.modules</groupId>
        <artifactId>deltaspike-jpa-module-api</artifactId>
        <version>${deltaspike.version}</version>
        <scope>compile</scope>
    </dependency>

    <dependency>
        <groupId>org.apache.deltaspike.modules</groupId>
        <artifactId>deltaspike-jpa-module-impl</artifactId>
        <version>${deltaspike.version}</version>
        <scope>runtime</scope>
    </dependency>

    <dependency>
        <groupId>ws.ament.hammock</groupId>
        <artifactId>dist-microprofile</artifactId>
        <version>${hammock.version}</version>
    </dependency>

    <dependency>
        <groupId>ws.ament.hammock</groupId>
        <artifactId>jpa-openjpa</artifactId>
        <version>${hammock.version}</version>
    </dependency>

    <dependency>
        <groupId>ws.ament.hammock</groupId>
        <artifactId>util-beanvalidation</artifactId>
        <version>${hammock.version}</version>
    </dependency>

    <dependency>
        <groupId>ws.ament.hammock</groupId>
        <artifactId>util-flyway</artifactId>
        <version>${hammock.version}</version>
    </dependency>

    <dependency>
        <groupId>ws.ament.hammock</groupId>
        <artifactId>swagger</artifactId>
        <version>${hammock.version}</version>
    </dependency>
</dependencies>

Without further ado, let us build and run the application right away (if you are curious what relational datastore the application is using, it is H2 with the database configured in-memory).

> mvn clean package
> java -jar target/eclipse-microprofile-hammock-0.0.1-SNAPSHOT-capsule.jar 

The best way to ensure that our people management RESTful web APIs are fully functional is to send a couple of requests to it:

>  curl -X POST http://localhost:10900/api/people -H "Content-Type: application\json" \
     -d '{"email": "[email protected]", "firstName": "John", "lastName": "Smith"}'

HTTP/1.1 201 Created
Location: http://localhost:10900/api/people/[email protected]
Content-Type: application/json

{
    "firstName":"John","
    "lastName":"Smith",
    "email":"[email protected]"
}

What about making sure the Bean Validation is working fine? To trigger that, let us send the partially prepared request.

>  curl  --X POST http://localhost:10900/api/people -H "Content-Type: application\json" \
     -d '{"firstName": "John", "lastName": "Smith"}'

HTTP/1.1 400 Bad Request
Content-Length: 0

The OpenAPI specification and pre-bundled Swagger UI distribution are also available at http://localhost:10900/index.html?url=http://localhost:10900/api/openapi.json.

So far so good but fairly speaking we have not talked about testing our application at all. How hard it would be to come up with the integration test for, let say, the scenario of adding a person? It turns out that the frameworks around testing Java EE applications have improved a lot. In particular, it is exceptionally easy to accomplish with Arquillian test framework (along with beloved JUnit and REST Assured). One real example is worth thousand words.

@RunWith(Arquillian.class)
@EnableRandomWebServerPort
public class PeopleApiTest {
    @ArquillianResource private URI uri;
    
    @Deployment
    public static JavaArchive createArchive() {
        return ShrinkWrap
            .create(JavaArchive.class)
            .addClasses(PeopleResource.class, PeopleApplication.class)
            .addClasses(PeopleServiceImpl.class, PeopleJpaRepository.class, PersistenceConfig.class)
            .addPackages(true, "org.apache.deltaspike");
    }
            
    @Test
    public void shouldAddNewPerson() throws Exception {
        final Person person = new Person("[email protected]", "John", "Smith");
        
        given()
            .contentType(ContentType.JSON)
            .body(person)
            .post(uri + "/api/people")
            .then()
            .assertThat()
            .statusCode(201)
            .body("email", equalTo("[email protected]"))
            .body("firstName", equalTo("John"))
            .body("lastName", equalTo("Smith"));
    }
}

Amazing, isn't it? It is actually a lot of fun to develop modern Java EE applications, someone may say, the Spring way! And in fact, the parallels with Spring are not coincidental since it was inspiring, is inspiring and undoubtedly is going to continue inspire a lot of innovations in the Java EE ecosystem.

How the future is looking like? I think, by all means bright, both for Jakarta EE and Eclipse Microprofile. The latter just approached the version 2.0 with tons of new specifications included, oriented to address the needs of the microservice architectures. It is awesome to witness these transformations happening.

The complete source of the project is available on Github.

Sunday, November 27, 2016

Keep your promises: contract-based testing for JAX-RS APIs

It's been a while since we talked about testing and applying effective TDD practices, particularly related to REST(ful) web services and APIs. But this topic should have never been forgotten, especially in the world where everyone is doing microservices, whatever it means, implies or takes.

To be fair, there are quite a lot of areas where microservice-based architecture shines and allows organizations to move and innovate much faster. But without a proper discipline, it also makes our systems fragile, as they become very loosely coupled. In today's post we are going to talk about contract-based testing and consumer-driven contracts as a practical and reliable techniques to ensure that our microservices fulfill their promises.

So, how does contract-based testing work? In nutshell, it is surprisingly simple technique and is guided by following steps:

  • provider (let say Service A) publishes its contact (or specification), the implementation may not even be available at this stage
  • consumer (let say Service B) follows this contract (or specification) to implement conversations with Service A
  • additionally, consumer introduces a test suite to verify its expectations regarding Service A contract fulfillment
In case of SOAP web services and APIs, things are obvious as there is an explicit contract in a form of WSDL file. But in case of REST(ful) APIs, there are a lot of different options around the corner (WADL, RAML, Swagger, ...) and still no agreement on the one. It may sound complicated but please don't get upset, because Pact is coming on the rescue!

Pact is family of frameworks for supporting consumer-driven contracts testing. There are many language bindings and implementations available, including JVM ones, JVM Pact and Scala-Pact. To evolve such a polyglot ecosystem, Pact also includes a dedicated specification so to provide interoperability between different implementations.

Great, Pact is there, the stage is set and we are ready to take off with some real code snippets. Let us assume we are developing a REST(ful) web API for managing people, using terrific Apache CXF and JAX-RS 2.0 specification. To keep things simple, we are going to introduce only two endpoints:

  • POST /people/v1 to create new person
  • GET /people/v1?email=<email> to find person by email address
Essentially, we may not bother and just communicate these minimal pieces of our service contract to everyone so let the consumers deal with that themselves (and indeed, Pact supports such a scenario). But surely, we are not like that, we do care and would like to document our APIs comprehensively, likely we are already familiar with Swagger. With that, here is our PeopleRestService.
@Api(value = "Manage people")
@Path("/people/v1")
@Consumes(MediaType.APPLICATION_JSON)
@Produces(MediaType.APPLICATION_JSON)
public class PeopleRestService {
    @GET
    @ApiOperation(value = "Find person by e-mail", 
        notes = "Find person by e-mail", response = Person.class)
    @ApiResponses({
        @ApiResponse(code = 404, 
            message = "Person with such e-mail doesn't exists", 
            response = GenericError.class)
    })
    public Response findPerson(
        @ApiParam(value = "E-Mail address to lookup for", required = true) 
        @QueryParam("email") final String email) {
        // implementation here
    }

    @POST
    @ApiOperation(value = "Create new person", 
        notes = "Create new person", response = Person.class)
    @ApiResponses({
        @ApiResponse(code = 201, 
            message = "Person created successfully", 
            response = Person.class),
        @ApiResponse(code = 409, 
            message = "Person with such e-mail already exists", 
            response = GenericError.class)
    })
    public Response addPerson(@Context UriInfo uriInfo, 
        @ApiParam(required = true) PersonUpdate person) {
        // implementation here
    }
}

The implementation details are not important at the moment, however let us take a look at the GenericError, PersonUpdate and Person classes as they are an integral part of our service contract.

@ApiModel(description = "Generic error representation")
public class GenericError {
    @ApiModelProperty(value = "Error message", required = true)
    private String message;
}

@ApiModel(description = "Person resource representation")
public class PersonUpdate {
    @ApiModelProperty(value = "Person's first name", required = true) 
    private String email;
    @ApiModelProperty(value = "Person's e-mail address", required = true) 
    private String firstName;
    @ApiModelProperty(value = "Person's last name", required = true) 
    private String lastName;
    @ApiModelProperty(value = "Person's age", required = true) 
    private int age;
}

@ApiModel(description = "Person resource representation")
public class Person extends PersonUpdate {
    @ApiModelProperty(value = "Person's identifier", required = true) 
    private String id;
}

Excellent! Once we have Swagger annotations in place and Apache CXF Swagger integration turned on, we could generate swagger.json specification file, bring it to live in Swagger UI and distribute to every partner or interested consumer.

Would be great if we could use this Swagger specification along with Pact framework implementation to serve as a service contract. Thanks to Atlassian, we are certainly able to do that using swagger-request-validator, a library for validating HTTP request/respons against a Swagger/OpenAPI specification which nicely integrates with Pact JVM as well.

Cool, now let us switch sides from provider to consumer and try to figure out what we can do having such Swagger specification in our hands. It turns out, we can do a lot of things. For example, let us take a look at the POST action, which creates new person. As a client (or consumer), we could express our expectations in such a form that having a valid payload submitted along with the request, we expect HTTP status code 201 to be returned by the provider and the response payload should contain a new person with identifier assigned. In fact, translating this statement into Pact JVM assertions is pretty straightforward.

@Pact(provider = PROVIDER_ID, consumer = CONSUMER_ID)
public PactFragment addPerson(PactDslWithProvider builder) {
    return builder
        .uponReceiving("POST new person")
        .method("POST")
        .path("/services/people/v1")
        .body(
            new PactDslJsonBody()
                .stringType("email")
                .stringType("firstName")
                .stringType("lastName")
                .numberType("age")
        )
        .willRespondWith()
        .status(201)
        .matchHeader(HttpHeaders.CONTENT_TYPE, MediaType.APPLICATION_JSON)
        .body(
            new PactDslJsonBody()
                .uuid("id")
                .stringType("email")
                .stringType("firstName")
                .stringType("lastName")
                .numberType("age")
        )
       .toFragment();
}

To trigger the contract verification process, we are going to use awesome JUnit and very popular REST Assured framework. But before that, let us clarify on what is PROVIDER_ID and CONSUMER_ID from the code snippet above. As you may expect, PROVIDER_ID is the reference to the contract specification. For simplicity, we would fetch Swagger specification from running PeopleRestService endpoint, luckily Spring Boot testing improvements make this task a no-brainer.

@RunWith(SpringJUnit4ClassRunner.class)
@SpringBootTest(webEnvironment = WebEnvironment.RANDOM_PORT, 
    classes = PeopleRestConfiguration.class)
public class PeopleRestContractTest {
    private static final String PROVIDER_ID = "People Rest Service";
    private static final String CONSUMER_ID = "People Rest Service Consumer";

    private ValidatedPactProviderRule provider;
    @Value("${local.server.port}")
    private int port;

    @Rule
    public ValidatedPactProviderRule getValidatedPactProviderRule() {
        if (provider == null) {
            provider = new ValidatedPactProviderRule("http://localhost:" + port + 
                "/services/swagger.json", null, PROVIDER_ID, this);
        }

        return provider;
    }
}

The CONSUMER_ID is just a way to identify the consumer, not much to say about it. With that, we are ready to finish up with our first test case:

@Test
@PactVerification(value = PROVIDER_ID, fragment = "addPerson")
public void testAddPerson() {
    given()
        .contentType(ContentType.JSON)
        .body(new PersonUpdate("[email protected]", "Tom", "Smith", 60))
        .post(provider.getConfig().url() + "/services/people/v1");
}

Awesome! As simple as that, just please notice the presence of @PactVerification annotation where we are referencing the appropriate verification fragment by name, in this case it points out to addPerson method we have introduced before.

Great, but ... what the point? Glad you are asking, because from now on any change in the contract which may not be backward compatible will break our test case. For example, if provider decides to remove the id property from the response payload, the test case will fail. Renaming the request payload properties, big no-no, again, test case will fail. Adding new path parameters? No luck, test case won't let it pass. You may go even further than that and fail on every contract change, even if it backward-compatible (using swagger-validator.properties for fine-tuning).

validation.response=ERROR
validation.response.body.missing=ERROR

No a very good idea but still, if you need it, it is there. Similarly, let us add a couple of more test cases for GET endpoint, starting from successful scenario, where person we are looking for exists, for example:

@Pact(provider = PROVIDER_ID, consumer = CONSUMER_ID)
public PactFragment findPerson(PactDslWithProvider builder) {
    return builder
        .uponReceiving("GET find person")
        .method("GET")
        .path("/services/people/v1")
        .query("[email protected]")
        .willRespondWith()
        .status(200)
        .matchHeader(HttpHeaders.CONTENT_TYPE, MediaType.APPLICATION_JSON)
        .body(
            new PactDslJsonBody()
                .uuid("id")
                .stringType("email")
                .stringType("firstName")
                .stringType("lastName")
                .numberType("age")
        )
        .toFragment();
}

@Test
@PactVerification(value = PROVIDER_ID, fragment = "findPerson")
public void testFindPerson() {
    given()
        .contentType(ContentType.JSON)
        .queryParam("email", "[email protected]")
        .get(provider.getConfig().url() + "/services/people/v1");
}

Please take a note that here we introduced query string verification using query("[email protected]") assertion. Following the possible outcomes, let us also cover the unsuccessful scenario, where person does not exist and we expect some error to be returned, along with 404 status code, for example:

@Pact(provider = PROVIDER_ID, consumer = CONSUMER_ID)
public PactFragment findNonExistingPerson(PactDslWithProvider builder) {
    return builder
        .uponReceiving("GET find non-existing person")
        .method("GET")
        .path("/services/people/v1")
        .query("[email protected]")
        .willRespondWith()
        .status(404)
        .matchHeader(HttpHeaders.CONTENT_TYPE, MediaType.APPLICATION_JSON)
        .body(new PactDslJsonBody().stringType("message"))
        .toFragment();
}

@Test
@PactVerification(value = PROVIDER_ID, fragment = "findNonExistingPerson")
public void testFindPersonWhichDoesNotExist() {
    given()
        .contentType(ContentType.JSON)
        .queryParam("email", "[email protected]")
        .get(provider.getConfig().url() + "/services/people/v1");
}

Really brilliant, maintainable, understandable and non-intrusive approach to address such a complex and important problems as contract-based testing and consumer-driven contracts. Hopefully, this somewhat new testing technique would help you to catch more issues during the development phase, way before they would have a chance to leak into production.

Thanks to Swagger we were able to take a few shortcuts, but in case you don't have such a luxury, Pact has quite rich specification which you are very welcome to learn and use. In any case, Pact JVM does a really great job in helping you out writing small and concise test cases.

The complete project sources are available on Github.