Google Guava v07 examples

We have something called Weekly Technology Workshops at TouK, that is, every Friday at 16:00 somebody has a presentation for everyone willing to come. We present stuff we learn and work on at home, but we also have a bulletin board with topics that people would like to listen about. Last week Maciej Próchniak had a talk about Clojure, this time a few folks asked for an introduction to Google Guava libraries.Since this was a dead simple task, I was happy to deliver.

WTF is Guava?

It’s a set of very simple, basic classes, that you end up writing yourself anyway. Think in terms of Apache commons, just by Google. Just to make your life a little bit easier.

There is an early (v04) presentation and there was a different one (in Polish) at Javarsowia 2010 by Wiktor Gworek.

At the time of writing this, the latest version is v07, it’s been mavenized and is available at a public maven repo.

Here’s a quick review of a few interesting things. Don’t expect anything fancy though, Guava is very BASIC.


@VisibleForTesting

A simple annotation that tells you why a particular property access restriction has been relaxed.

A common trick to use in testing is to relax access restrictions to default for a particular property, so that you can use it in a unit test, which resides in the same package (though in different catalog). Whether you thing it’s good or bad, remember to give a hint about that to the developer.

Consider:

public class User {
    private Long id;
    private String firstName;
    private String lastName;
    String login;

Why is login package scoped?

public class User {
    private Long id;
    private String firstName;
    private String lastName;
    @VisibleForTesting String login;

Ah, that’s why.


Preconditions

Guava has a few preconditions for defensive programming (Design By Contract), but they are not quite as good as what Apache Commons / Spring framework has. One thing interesting is that Guava solution returns the object, so could be inlined. Consider:

Using hand written preconditions:

public User(Long id, String firstName, String lastName, String login) {
        validateParameters(id, firstName, lastName, login);
        this.id = id;
        this.firstName = firstName;
        this.lastName = lastName;
        this.login = login.toLowerCase();
    }

    private void validateParameters(Long id, String firstName, String lastName, String login) {
        if(id == null ) {
            throw new IllegalArgumentException("id cannot be null");
        }

        if(firstName == null || firstName.length() == 0) {
            throw new IllegalArgumentException("firstName cannot be empty");
        }

        if(lastName == null || lastName.length() == 0) {
            throw new IllegalArgumentException("lastName cannot be empty");
        }

        if(login == null || login.length() == 0) {
            throw new IllegalArgumentException("login cannot be empty");
        }
    }

Using guava preconditions:

public void fullyImplementedGuavaConstructorWouldBe(Long id, String firstName, String lastName, String login) {
        this.id = checkNotNull(id);
        this.firstName = checkNotNull(firstName);
        this.lastName = checkNotNull(lastName);
        this.login = checkNotNull(login);

        checkArgument(firstName.length() > 0);
        checkArgument(lastName.length() > 0);
        checkArgument(login.length() > 0);
    }

(Thanks Yom for noticing that checkNotNull must go before checkArgument, though it makes it a bit unintuitive)

Using spring or apache commons preconditions (the use looks exactly the same for both libraries):

public void springConstructorWouldBe(Long id, String firstName, String lastName, String login) {
        notNull(id); hasText(firstName); hasText(lastName); hasText(login);
        this.id = id;
        this.firstName = firstName;
        this.lastName = lastName;
        this.login = login;
    }

CharMatcher

For people who hate regexp or just want a simple and good looking object style pattern matching solution.

Examples:

And/or ease of use

        String input = "This invoice has an id of 192/10/10";
        CharMatcher charMatcher = CharMatcher.DIGIT.or(CharMatcher.is('/'));
        String output = charMatcher.retainFrom(input);

output is: 192/10/10

Negation:

        String input = "DO NOT scream at me!";
        CharMatcher charMatcher = CharMatcher.JAVA_LOWER_CASE.or(CharMatcher.WHITESPACE).negate();
        String output = charMatcher.retainFrom(input);

output is: DONOT!

Ranges:

        String input = "DO NOT scream at me!";
        CharMatcher charMatcher = CharMatcher.inRange('m', 's').or(CharMatcher.is('a').or(CharMatcher.WHITESPACE));
        String output = charMatcher.retainFrom(input);

output is: sram a m

Joiner / Splitter

As the names suggest, it’s string joining/splitting done the right way, although I find the inversion of calls a bit… oh well, it’s java.

        String[] fantasyGenres = {"Space Opera", "Horror", "Magic realism", "Religion"};
        String joined = Joiner.on(", ").join(fantasyGenres);

Output: Space Opera, Horror, Magic realism, Religion

You can skip nulls:

        String[] fantasyGenres = {"Space Opera", null, "Horror", "Magic realism", null, "Religion"};
        String joined = Joiner.on(", ").skipNulls().join(fantasyGenres);

Output: Space Opera, Horror, Magic realism, Religion

You can fill nulls:

        String[] fantasyGenres = {"Space Opera", null, "Horror", "Magic realism", null, "Religion"};
        String joined = Joiner.on(", ").useForNull("NULL!!!").join(fantasyGenres);

Output: Space Opera, NULL!!!, Horror, Magic realism, NULL!!!, Religion

You can join maps

        Map map = newHashMap();
        map.put(1, "Space Opera");
        map.put(2, "Horror");
        map.put(3, "Magic realism");
        String joined = Joiner.on(", ").withKeyValueSeparator(" -> ").join(map);

Output: 1 → Space Opera, 2 → Horror, 3 → Magic realism

Split returns Iterable instead of JDK arrays:

        String input = "Some very stupid data with ids of invoces like 121432, 3436534 and 8989898 inside";
        Iterable splitted = Splitter.on(" ").split(input);

Split does fixed length splitting, although you cannot give a different length for each “column” which makes it’s use a bit limited while parsing some badly exported excels.

        String input =
                "A  1  1  1  1\n" +
                "B  1  2  2  2\n" +
                "C  1  2  3  3\n" +
                "D  1  2  5  3\n" +
                "E  3  2  5  4\n" +
                "F  3  3  7  5\n" +
                "G  3  3  7  5\n" +
                "H  3  3  9  7";
        Iterable splitted = Splitter.fixedLength(3).trimResults().split(input);

You can use CharMatcher while splitting

        String input = "Some very stupid data with ids of invoces like 123231/fv/10/2010, 123231/fv/10/2010 and 123231/fv/10/2010";
        Iterable splitted = Splitter.on(CharMatcher.DIGIT.negate())
                                            .trimResults()
                                            .omitEmptyStrings()
                                            .split(input);

Predicates / Functions

Predicates alone are not much, it’s just an interface with a method that returns true, but if you combine predicates with functions and Collections2 (a guava class that simplifies working on collections), you get a nice tool in your toolbox.

But let’s start with basic predicate use. Imagine we want to find whether there are users who have logins with digits inside. The inocation would be (returns boolean):

Predicates.in(users).apply(shouldNotHaveDigitsInLoginPredicate);

And the predicate looks like that

public class ShouldNotHaveDigitsInLoginPredicate implements Predicate {
    @Override
    public boolean apply(User user) {
        checkNotNull(user);
        return CharMatcher.DIGIT.retainFrom(user.login).length() == 0;
    }    
}

Now lets add a function that will transform a user to his full name:

public class FullNameFunction implements Function {
    @Override
    public String apply(User user) {
        checkNotNull(user);
        return user.getFirstName() + " " + user.getLastName();
    }    
}

You can invoke it using static method transform:

List users = newArrayList(new User(1L, "sylwek", "stall", "rambo"),
  new User(2L, "arnold", "schwartz", "commando"));

List fullNames = transform(users, new FullNameFunction());

And now lets combine predicates with functions to print names of users that have logins which do not contain digits:

List users = newArrayList(new User(1L, "sylwek", "stall", "rambo"), 
  new User(2L, "arnold", "schwartz", "commando"), 
  new User(3L, "hans", "kloss", "jw23"));

Collection usersWithoutDigitsInLogin = filter(users, new ShouldNotHaveDigitsInLoginPredicate());
String names = Joiner.on("\n").join( transform(usersWithoutDigitsInLogin, new FullNameFunction()) );

What we do not get: fold (reduce) and tuples. Oh well, you’d probably turn to Java Functional Library anyway, if you wanted functions in Java, right?

CaseFormat

Ever wanted to turn those ugly PHP Pear names into nice java/cpp style with one liner? No? Well, anyway, you can:

String pearPhpName = "Really_Fucked_Up_PHP_PearConvention_That_Looks_UGLY_because_of_no_NAMESPACES";
String javaAndCPPName = CaseFormat.UPPER_UNDERSCORE.to(CaseFormat.UPPER_CAMEL , pearPhpName);

Output: ReallyFuckedUpPhpPearconventionThatLooksUglyBecauseOfNoNamespaces

But since Oracle has taken over Sun, you may actually want to turn those into sql style, right?

        String sqlName = CaseFormat.UPPER_CAMEL.to(CaseFormat.LOWER_UNDERSCORE, javaAndCPPName);

Output: really_fucked_up_php_pearconvention_that_looks_ugly_because_of_no_namespaces

Collections

Guava has a superset of Google collections library 1.0, and this indeed is a very good reason to include this dependency in your poms. I won’t even try to describe all the features, but just to point out a few nice things:

  • you have an Immutable version of pretty much everything
  • you get a few nice static and statically typed methods on common types like Lists, Sets, Maps, ObjectArrays, which include:
    • easy way of creating based on return type: e.g. newArrayList
    • transform (way to apply functions that returns Immutable version)
    • partition (paging)
    • reverse

And now for a few more interesting collections.
Mutlimaps

Mutlimap is basically a map that can have many values for a single key. Ever had to create a Map> in your code? You don’t have to anymore.

Multimap multimap = HashMultimap.create();
        multimap.put(1, "a");
        multimap.put(2, "b");
        multimap.put(3, "c");
        multimap.put(1, "a2");

There are of course immutable implementations as well: ImmutableListMultimap, ImmutableSetMultomap, etc.

You can construct immutables either in line (up to 5 elements) or using a builder:

Multimap multimap = ImmutableSetMultimap.of(1, "a", 2, "b", 3, "c", 1, "a2"); 
Multimap multimap = new ImmutableSetMultimap.Builder()
        .put(1, "a")
        .put(2, "b")
        .put(3, "c")
        .put(1, "a2")
        .build();

BiMap

BiMap is a map that have only unique values. Consider this:

@Test(expected = IllegalArgumentException.class)
public void biMapShouldOnlyHaveUniqueValues() {
 BiMap biMap = HashBiMap.create();
 biMap.put(1, "a");
 biMap.put(2, "b");
 biMap.put(3, "a"); //argh! an exception
}

That allows you to inverse the map, so the values become key and the other way around:

BiMap biMap = HashBiMap.create();
biMap.put(1, "a");
biMap.put(2, "b");
biMap.put(3, "c");

BiMap invertedMap = biMap.inverse();

Not sure what I’d actually want to use it for.

Constraints

This allows you to add constraint checking on a collection, so that only values which pass the constraint may be added.

Imagine we want a collections of users with first letter ‘r’ in their logins.

Constraint loginMustStartWithR = new Constraint() {
    @Override
    public User checkElement(User user) {
        checkNotNull(user);

        if(!user.login.startsWith("r")) {
            throw new IllegalArgumentException("GTFO, you are not Rrrrrrrrr");
        }

        return user;
    }
};

And now for a test:

@Test(expected = IllegalArgumentException.class)
public void shouldConstraintCollection() {
 //given
 Collection users = newArrayList(new User(1L, "john", "rambo", "rambo"));
 Collection usersThatStartWithR = constrainedCollection(users, loginMustStartWithR);

 //when
 usersThatStartWithR.add(new User(2L, "arnold", "schwarz", "commando"));
}

You also get notNull constraint out of the box:

//notice it's not an IllegalArgumentException :( 
@Test(expected = NullPointerException.class)
public void notNullConstraintShouldWork() {
 //given
 Collection users = newArrayList(1);
 Collection notNullCollection = constrainedCollection(users, notNull());

 //when
 notNullCollection.add(null);
}

Thing to remember: constraints are not checking the data already present in a collection.

Tables

Just as expected, a table is a collection with columns, rows and values. No more Map> I guess. The usage is simple and you can transpose:

Table table = HashBasedTable.create();
table.put(1, "a", "1a");
table.put(1, "b", "1b");
table.put(2, "a", "2a");
table.put(2, "b", "2b");

Table transponedTable = Tables.transpose(table);

That’s all, folks. I didn’t present util.concurent, primitives, io and net packages, but you probably already know what to expect.

You May Also Like

Integration testing custom validation constraints in Jersey 2

I recently joined a team trying to switch a monolithic legacy system into set of RESTful services in Java. They decided to use latest 2.x version of Jersey as a REST container which was not a first choice for me, since I’m not a big fan of JSR-* specs. But now I must admit that JAX-RS 2.x is doing things right: requires almost zero boilerplate code, support auto-discovery of features and prefers convention over configuration like other modern frameworks. Since the spec is still young, it’s hard to find good tutorials and kick-off projects with some working code. I created jersey2-starter project on GitHub which can be used as starting point for your own production-ready RESTful service. In this post I’d like to cover how to implement and integration test your own validation constraints of REST resources.

Custom constraints

One of the issues which bothers me when coding REST in Java is littering your class model with annotations. Suppose you want to build a simple Todo list REST service, when using Jackson, validation and Spring Data, you can easily end up with this as your entity class:

@Document
public class Todo {
    private Long id;
    @NotNull
    private String description;
    @NotNull
    private Boolean completed;
    @NotNull
    private DateTime dueDate;

    @JsonCreator
    public Todo(@JsonProperty("description") String description, @JsonProperty("dueDate") DateTime dueDate) {
        this.description = description;
        this.dueDate = dueDate;
        this.completed = false;
    }
    // getters and setters
}

Your domain model is now effectively blured by messy annotations almost everywhere. Let’s see what we can do with validation constraints (@NotNulls). Some may say that you could introduce some DTO layer with own validation rules, but it conflicts for me with pure REST API design, which stands that you operate on resources which should map to your domain classes. On the other hand - what does it mean that Todo object is valid? When you create a Todo you should provide a description and due date, but what when you’re updating? You should be able to change any of description, due date (postponing) and completion flag (marking as done) - but you should provide at least one of these as valid modification. So my idea is to introduce custom validation constraints, different ones for creation and modification:

@Target({TYPE, PARAMETER})
@Retention(RUNTIME)
@Constraint(validatedBy = ValidForCreation.Validator.class)
public @interface ValidForCreation {
    //...
    class Validator implements ConstraintValidator<ValidForCreation, Todo> {
    /...
        @Override
        public boolean isValid(Todo todo, ConstraintValidatorContext constraintValidatorContext) {
            return todo != null
                && todo.getId() == null
                && todo.getDescription() != null
                && todo.getDueDate() != null;
        }
    }
}

@Target({TYPE, PARAMETER})
@Retention(RUNTIME)
@Constraint(validatedBy = ValidForModification.Validator.class)
public @interface ValidForModification {
    //...
    class Validator implements ConstraintValidator<ValidForModification, Todo> {
    /...
        @Override
        public boolean isValid(Todo todo, ConstraintValidatorContext constraintValidatorContext) {
            return todo != null
                && todo.getId() == null
                && (todo.getDescription() != null || todo.getDueDate() != null || todo.isCompleted() != null);
        }
    }
}

And now you can move validation annotations to the definition of a REST endpoint:

@POST
@Consumes(APPLICATION_JSON)
public Response create(@ValidForCreation Todo todo) {...}

@PUT
@Consumes(APPLICATION_JSON)
public Response update(@ValidForModification Todo todo) {...}

And now you can remove those NotNulls from your model.

Integration testing

There are in general two approaches to integration testing:

  • test is being run on separate JVM than the app, which is deployed on some other integration environment
  • test deploys the application programmatically in the setup block.

Both of these have their pros and cons, but for small enough servoces, I personally prefer the second approach. It’s much easier to setup and you have only one JVM started, which makes debugging really easy. You can use a generic framework like Arquillian for starting your application in a container environment, but I prefer simple solutions and just use emdedded Jetty. To make test setup 100% production equivalent, I’m creating full Jetty’s WebAppContext and have to resolve all runtime dependencies for Jersey auto-discovery to work. This can be simply achieved with Maven resolved from Shrinkwrap - an Arquillian subproject:

    WebAppContext webAppContext = new WebAppContext();
    webAppContext.setResourceBase("src/main/webapp");
    webAppContext.setContextPath("/");
    File[] mavenLibs = Maven.resolver().loadPomFromFile("pom.xml")
                .importCompileAndRuntimeDependencies()
                .resolve().withTransitivity().asFile();
    for (File file: mavenLibs) {
        webAppContext.getMetaData().addWebInfJar(new FileResource(file.toURI()));
    }
    webAppContext.getMetaData().addContainerResource(new FileResource(new File("./target/classes").toURI()));

    webAppContext.setConfigurations(new Configuration[] {
        new AnnotationConfiguration(),
        new WebXmlConfiguration(),
        new WebInfConfiguration()
    });
    server.setHandler(webAppContext);

(this Stackoverflow thread inspired me a lot here)

Now it’s time for the last part of the post: parametrizing our integration tests. Since we want to test validation constraints, there are many edge paths to check (and make your code coverage close to 100%). Writing one test per each case could be a bad idea. Among the many solutions for JUnit I’m most convinced to the Junit Params by Pragmatists team. It’s really simple and have nice concept of JQuery-like helper for creating providers. Here is my tests code (I’m also using builder pattern here to create various kinds of Todos):

@Test
@Parameters(method = "provideInvalidTodosForCreation")
public void shouldRejectInvalidTodoWhenCreate(Todo todo) {
    Response response = createTarget().request().post(Entity.json(todo));

    assertThat(response.getStatus()).isEqualTo(BAD_REQUEST.getStatusCode());
}

private static Object[] provideInvalidTodosForCreation() {
    return $(
        new TodoBuilder().withDescription("test").build(),
        new TodoBuilder().withDueDate(DateTime.now()).build(),
        new TodoBuilder().withId(123L).build(),
        new TodoBuilder().build()
    );
}

OK, enough of reading, feel free to clone the project and start writing your REST services!

I recently joined a team trying to switch a monolithic legacy system into set of RESTful services in Java. They decided to use latest 2.x version of Jersey as a REST container which was not a first choice for me, since I’m not a big fan of JSR-* specs. But now I must admit that JAX-RS 2.x is doing things right: requires almost zero boilerplate code, support auto-discovery of features and prefers convention over configuration like other modern frameworks. Since the spec is still young, it’s hard to find good tutorials and kick-off projects with some working code. I created jersey2-starter project on GitHub which can be used as starting point for your own production-ready RESTful service. In this post I’d like to cover how to implement and integration test your own validation constraints of REST resources.

Custom constraints

One of the issues which bothers me when coding REST in Java is littering your class model with annotations. Suppose you want to build a simple Todo list REST service, when using Jackson, validation and Spring Data, you can easily end up with this as your entity class:

@Document
public class Todo {
    private Long id;
    @NotNull
    private String description;
    @NotNull
    private Boolean completed;
    @NotNull
    private DateTime dueDate;

    @JsonCreator
    public Todo(@JsonProperty("description") String description, @JsonProperty("dueDate") DateTime dueDate) {
        this.description = description;
        this.dueDate = dueDate;
        this.completed = false;
    }
    // getters and setters
}

Your domain model is now effectively blured by messy annotations almost everywhere. Let’s see what we can do with validation constraints (@NotNulls). Some may say that you could introduce some DTO layer with own validation rules, but it conflicts for me with pure REST API design, which stands that you operate on resources which should map to your domain classes. On the other hand - what does it mean that Todo object is valid? When you create a Todo you should provide a description and due date, but what when you’re updating? You should be able to change any of description, due date (postponing) and completion flag (marking as done) - but you should provide at least one of these as valid modification. So my idea is to introduce custom validation constraints, different ones for creation and modification:

@Target({TYPE, PARAMETER})
@Retention(RUNTIME)
@Constraint(validatedBy = ValidForCreation.Validator.class)
public @interface ValidForCreation {
    //...
    class Validator implements ConstraintValidator<ValidForCreation, Todo> {
    /...
        @Override
        public boolean isValid(Todo todo, ConstraintValidatorContext constraintValidatorContext) {
            return todo != null
                && todo.getId() == null
                && todo.getDescription() != null
                && todo.getDueDate() != null;
        }
    }
}

@Target({TYPE, PARAMETER})
@Retention(RUNTIME)
@Constraint(validatedBy = ValidForModification.Validator.class)
public @interface ValidForModification {
    //...
    class Validator implements ConstraintValidator<ValidForModification, Todo> {
    /...
        @Override
        public boolean isValid(Todo todo, ConstraintValidatorContext constraintValidatorContext) {
            return todo != null
                && todo.getId() == null
                && (todo.getDescription() != null || todo.getDueDate() != null || todo.isCompleted() != null);
        }
    }
}

And now you can move validation annotations to the definition of a REST endpoint:

@POST
@Consumes(APPLICATION_JSON)
public Response create(@ValidForCreation Todo todo) {...}

@PUT
@Consumes(APPLICATION_JSON)
public Response update(@ValidForModification Todo todo) {...}

And now you can remove those NotNulls from your model.

Integration testing

There are in general two approaches to integration testing:

  • test is being run on separate JVM than the app, which is deployed on some other integration environment
  • test deploys the application programmatically in the setup block.

Both of these have their pros and cons, but for small enough servoces, I personally prefer the second approach. It’s much easier to setup and you have only one JVM started, which makes debugging really easy. You can use a generic framework like Arquillian for starting your application in a container environment, but I prefer simple solutions and just use emdedded Jetty. To make test setup 100% production equivalent, I’m creating full Jetty’s WebAppContext and have to resolve all runtime dependencies for Jersey auto-discovery to work. This can be simply achieved with Maven resolved from Shrinkwrap - an Arquillian subproject:

    WebAppContext webAppContext = new WebAppContext();
    webAppContext.setResourceBase("src/main/webapp");
    webAppContext.setContextPath("/");
    File[] mavenLibs = Maven.resolver().loadPomFromFile("pom.xml")
                .importCompileAndRuntimeDependencies()
                .resolve().withTransitivity().asFile();
    for (File file: mavenLibs) {
        webAppContext.getMetaData().addWebInfJar(new FileResource(file.toURI()));
    }
    webAppContext.getMetaData().addContainerResource(new FileResource(new File("./target/classes").toURI()));

    webAppContext.setConfigurations(new Configuration[] {
        new AnnotationConfiguration(),
        new WebXmlConfiguration(),
        new WebInfConfiguration()
    });
    server.setHandler(webAppContext);

(this Stackoverflow thread inspired me a lot here)

Now it’s time for the last part of the post: parametrizing our integration tests. Since we want to test validation constraints, there are many edge paths to check (and make your code coverage close to 100%). Writing one test per each case could be a bad idea. Among the many solutions for JUnit I’m most convinced to the Junit Params by Pragmatists team. It’s really simple and have nice concept of JQuery-like helper for creating providers. Here is my tests code (I’m also using builder pattern here to create various kinds of Todos):

@Test
@Parameters(method = "provideInvalidTodosForCreation")
public void shouldRejectInvalidTodoWhenCreate(Todo todo) {
    Response response = createTarget().request().post(Entity.json(todo));

    assertThat(response.getStatus()).isEqualTo(BAD_REQUEST.getStatusCode());
}

private static Object[] provideInvalidTodosForCreation() {
    return $(
        new TodoBuilder().withDescription("test").build(),
        new TodoBuilder().withDueDate(DateTime.now()).build(),
        new TodoBuilder().withId(123L).build(),
        new TodoBuilder().build()
    );
}

OK, enough of reading, feel free to clone the project and start writing your REST services!