Kotlin Data Access Object

Even the most trivial of computer programs work with data. In many cases, the user will wish to save data and reuse it between one run of the program and a later session. Since different systems handle data differently, the user may need to save data in multiple formats for compatibility purposes. The program should know how to not only persist data but also read data from a variety of supported formats.

Let’s consider a word processes. When we write a document in a word processor, we may normally save documents in the word processor’s default file format. Later on, we may wish to share the document with another coworker or friend, but they have a different word processor than what we are using. The solution may be to use the word processor’s export feature to convert our document from the word processor’s default format to the file format our friend’s word processor is using.

Converting data isn’t just an issue for desktop programs either. We may have a web application deployed that may store data in an RBDMS but have to export the same data to XML or JSON. Likewise, it’s very likely a web application may need to consume JSON and export data as a CSV format. Clearly, there is plenty of need for an application to be flexible about file formats.

That means we should not tie the persistent mechanism to a data structure. It might seem to go against the OOP principle of encapsulation where each object is responsible for its own data but think about the implications of such a design. If we write the persistence logic into a class, the class is tied to a particular file format. What happens when the class needs to read and write to a different file format? We could add additional persistence mechanisms to the class, but eventually, the class becomes bloated as we add more and more persistence schemes to it.

Another approach might be to define abstract methods for saving and retrieving data, but this is equally as bad of an approach. For one thing, are we really going to create an entire class hierarchy just for reading and writing data? Furthermore, we have no means with which to enforce a certain storage mechanism since all instances of such a class would resolve their storage logic using virtual methods. Finally, we would most likely need to convert instances of one subclass to another subclass in order to switch between storage mechanisms, which could send us down the rabbit hole of deep cloning objects.

If you think about it, storing and retrieving data is a completely separate concern of the application. A data object should never end up being responsible for its own persistence. That needs to be the concern of a completely different class or set of classes. Thus we end up with the data access pattern.

The data access pattern relies on a transfer object to hold the data. The transfer object is passed between the view (which is normally the UI) and the source of the data. Kotlin has a special data class that we can use for this specific purpose. Let’s have a look at an example.

/**
 * This a model class that is persisted to disk in this program
 */
data class Cook(val fName : String,
                val lName : String,
                val position : String,
                val age : Int) : Serializable

Koltin data classes get a built-in implementation of hashCode(), equals(), and toString(). We are free to add additional methods to them if needed. We also have this class implementing Serializable for a later demonstration. The important part to note about the Cook class is that it does not handle its own persistence. That is done by another class that is specific for this purpose.

Once we have our transfer object, we can begin by defining our persistence classes. Since we plan on using different formats for reading and writing data, we should use an interface as an abstraction point.

/**
 * This interface describes the kinds of Data Access Operations available
 */
interface CookDao {
    fun save(c : Cook, outStream: OutputStream)

    fun read(inStream: InputStream) : Cook
}

Our CookDao interface defines two methods. The first method, save(), takes a Cook object and an OuputStream. The Cook object is, of course, the transfer object. As for the OutputStream, it’s best to use OutputStream rather than File because it allows this Dao class to work with non-file streams such as network sockets. The DAO class should be concerned with how the object is persisted and retrieved, but it should not be coupled to a particular source. This keeps it flexible and allows us to send and store data on File Systems, Network Sockets, Http Responses, etc.

The same principle holds true for the read() function as well. This method takes an InputStream, the reciprocal class for OutputStream, and returns a Cook object. This allows us to create a Cook from any input stream. Once again, the source of the InputStream isn’t important to the class, only that it contains the data needed to create a Cook object.

Now that we have our interface, let’s look out our implementations. At first, our application wishes to store Cooks as Serialized Java Objects. Let’s create a version of CookDao that accomplishes this task.

/**
 * Implementation of CookDao that uses JVM serialization
 */
class SerializedCookDao : CookDao{
    override fun save(c: Cook, outStream: OutputStream) {
        val o = ObjectOutputStream(outStream)
        outStream.use {
            o.writeObject(c)
        }
    }

    override fun read(inStream: InputStream) : Cook{
        val i = ObjectInputStream(inStream)
        inStream.use {
            return i.readObject() as Cook
        }
    }
}

The SerializedCookDao implements CookDao and stores Cook as a Serialized Java object. When we wish to restore the Cook, we use the readObject() method found on ObjectInputStream to restore the Cook. Either way, the application at large isn’t concerned about how cook is persisted and restored.

Later on, we decide to support command separated values format or CSV. We don’t need to change any client code to accomplish such as task. All we need to do is define another class that implements CookDao.

/**
 * Implementation of CookDao that converts Cooks to a CSV file
 */
class CsvCookDao : CookDao {

    //Private extension function on Cook for creating
    //CSV files
    private fun Cook.toCSV() : String {
        return "${this.fName},${this.lName},${this.age},${this.position}"
    }

    //Private function to convert a CSV line to a Cook
    private fun parseCsv(csv : String) : Cook{
        val parts = csv.split(",")
        return Cook(fName = parts[0],
                    lName = parts[1],
                    age = parts[2].toInt(),
                    position = parts[3])
    }

    override fun save(c: Cook, outStream: OutputStream) {
        outStream.use {
            PrintWriter(outStream, true).println(c.toCSV())
        }
    }

    override fun read(inStream: InputStream): Cook {
        inStream.use {
            val sc = Scanner(inStream)
            return parseCsv(sc.nextLine())
        }
    }
}

The CsvCookDao class does the job. There are a couple of things to note about this class that makes it more interesting. The first is the extension function Cook.toCSV(). Kotlin extension functions let us add extra functionality to a class. We could have added a toCSV() method to Cook, but let’s think about the implications of such a design. For one thing, only CsvCookDao is concerned about making a Cook into a line of CSV. If we added toCSV() to Cook, then we are saying that all Cook objects should be able to turn themselves into CSV at any time.

That’s bad because we are violating the separation of concerns principle again. We don’t want Cook to concern itself with persistence. That’s the job of our DAO classes. Thus, our CsvCookDao gets a private method to convert Cooks into CSV. Likewise, we have the parseCsv function which also turns CSV back into Cooks. We could violate the separation of concerns by adding a constructor to the Cook class, but that would be equally as bad as adding a toCSV() method.

Now that we have our DAO classes, we need a way to pass Cooks from the view to the DAO. We can define a service class for this purpose.


/**
 * CookService uses Kotlin's delegation mechanism. CookService will have
 * all of the same methods as CookDao but the implementation will depend
 * on the CookDao that was provided
 */
class CookService(private val cookDao: CookDao) : CookDao by cookDao

The CookService class is powerful but incredibly compact. Instances of this class are using Kotlin’s delegation mechanism where all of the methods of CookService are wrapped by methods found in CookDao. It’s this mechanism that lets our application switch between serialization and CSV so easily. The view will use CookService. The CookService is created by passing an instance of CookDao to the constructor of CookService. Whichever CookDao is used will determine the data format the application is currently using!

Let’s have a look at the final portion of the application to see this in action.

fun saveAndRestore(bob : Cook, cookService : CookService, inStream : InputStream, outStream : OutputStream){
    println("Bob before saving => " + bob)

    cookService.save(bob, outStream)

    var restoredBob = cookService.read(inStream)
    println("Bob after restoring => " + restoredBob)
}

fun createIfNeeded(name : String) : File{
    val f = File(name)
    if(!f.exists()){
        f.createNewFile()
    }
    return f
}

fun main(args : Array<String>){
    val bob = Cook("Bob", "Belcher", "Owner", 45)
    println("Using CSV")
    saveAndRestore(bob,
            CookService(CsvCookDao()), //Application is using CSV
            FileInputStream(createIfNeeded("bob.csv")),
            FileOutputStream(createIfNeeded("bob.csv")))
    println()
    println("Using serialization")
    saveAndRestore(bob,
            CookService(SerializedCookDao()), //Application is using Serialization
            FileInputStream(createIfNeeded("bob.ser")),
            FileOutputStream(createIfNeeded("bob.ser")))
}

The saveAndRestore function does the job of saving and restoring a Cook object. However, it has no idea of where or how a Cook is handled. The saveAndRestore function interacts soley with CookService. The CookService objects are created in the main method. When a CsvCookDao is used in the CookService constructor, the Cooks are saved in CSV format. When SerialiazedCookDao is used instead, the application will use JVM serialization to save and restore a Cook.

It’s easy to imagine how easily this program can be extended later on. Suppose we which to support XML. All we need to do is create a new CookDao class that handles the transformation of a Cook object to and from XML. Later on, we would pass this CookDao class to the constructor of CookService and the rest of the application would continue to work. In this fashion, we can easily continue to add additional file formats as needs change.

Putting it Together

Here is the program in its entirety followed by output.

package ch4.dataacesspattern

import java.io.*
import java.util.*

/**
 * This a model class that is persisted to disk in this program
 */
data class Cook(val fName : String,
                val lName : String,
                val position : String,
                val age : Int) : Serializable

/**
 * This interface describes the kinds of Data Access Operations available
 */
interface CookDao {
    fun save(c : Cook, outStream: OutputStream)

    fun read(inStream: InputStream) : Cook
}

/**
 * Implementation of CookDao that uses JVM serialization
 */
class SerializedCookDao : CookDao{
    override fun save(c: Cook, outStream: OutputStream) {
        val o = ObjectOutputStream(outStream)
        outStream.use {
            o.writeObject(c)
        }
    }

    override fun read(inStream: InputStream) : Cook{
        val i = ObjectInputStream(inStream)
        inStream.use {
            return i.readObject() as Cook
        }
    }
}

/**
 * Implementation of CookDao that converts Cooks to a CSV file
 */
class CsvCookDao : CookDao {

    //Private extension function on Cook for creating
    //CSV files
    private fun Cook.toCSV() : String {
        return "${this.fName},${this.lName},${this.age},${this.position}"
    }

    //Private function to convert a CSV line to a Cook
    private fun parseCsv(csv : String) : Cook{
        val parts = csv.split(",")
        return Cook(fName = parts[0],
                    lName = parts[1],
                    age = parts[2].toInt(),
                    position = parts[3])
    }

    override fun save(c: Cook, outStream: OutputStream) {
        outStream.use {
            PrintWriter(outStream, true).println(c.toCSV())
        }
    }

    override fun read(inStream: InputStream): Cook {
        inStream.use {
            val sc = Scanner(inStream)
            return parseCsv(sc.nextLine())
        }
    }
}

/**
 * CookService uses Kotlin's delegation mechanism. CookService will have
 * all of the same methods as CookDao but the implementation will depend
 * on the CookDao that was provided
 */
class CookService(private val cookDao: CookDao) : CookDao by cookDao

fun saveAndRestore(bob : Cook, cookService : CookService, inStream : InputStream, outStream : OutputStream){
    println("Bob before saving => " + bob)

    cookService.save(bob, outStream)

    var restoredBob = cookService.read(inStream)
    println("Bob after restoring => " + restoredBob)
}

fun createIfNeeded(name : String) : File{
    val f = File(name)
    if(!f.exists()){
        f.createNewFile()
    }
    return f
}

fun main(args : Array<String>){
    val bob = Cook("Bob", "Belcher", "Owner", 45)
    println("Using CSV")
    saveAndRestore(bob,
            CookService(CsvCookDao()), //Application is using CSV
            FileInputStream(createIfNeeded("bob.csv")),
            FileOutputStream(createIfNeeded("bob.csv")))
    println()
    println("Using serialization")
    saveAndRestore(bob,
            CookService(SerializedCookDao()), //Application is using Serialization
            FileInputStream(createIfNeeded("bob.ser")),
            FileOutputStream(createIfNeeded("bob.ser")))
}

Output

Using CSV
Bob before saving => Cook(fName=Bob, lName=Belcher, position=Owner, age=45)
Bob after restoring => Cook(fName=Bob, lName=Belcher, position=Owner, age=45)

Using serialization
Bob before saving => Cook(fName=Bob, lName=Belcher, position=Owner, age=45)
Bob after restoring => Cook(fName=Bob, lName=Belcher, position=Owner, age=45)
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Observer Pattern in Kotlin

JDK provides java.util.Observable and java.util.Observer as an abstract class / interface combination that allows an easy mechanism with which to implement the observer pattern. The framework allows one class to monitor changes in another class and react as needed to the changes. By using the class and interface provided in JDK, we can loosely couple one class to another while still maintaining the observer pattern.

We are going to use three classes in this example: Burger, Bob, and Tina. Bob is a cook who cooks Burgers. Tina is a server who serves the Burgers, and Burger is the object that is passed between Bob and Tina. Bob will notify Tina when a burger is ready, but he doesn’t actually know anything about Tina. All Bob knows (or cares about) is that Tina is an observer.

Let’s begin with both Burger and Bob (since Burger is one line of code).

class Burger(val name: String)

class Bob : Observable() {

    val name = "Bob"

    fun cookBurger(name : String){
        var burger = Burger(name)

        //Call setChanges() prior to calling notifyObservers()
        setChanged() //Inherited from Observable()
        notifyObservers(burger) //Inherited from Observable()
    }
}

We see here that Bob extends Observable. Observable is an abstract class found in the java.util package. In the cookBurger method, Bob creates an new instance of Burger and then calls setChanged(), a method defined in Observable. After calling setChanged(), Bob calls notifyObservers(), which also comes from Observable. All registered Observer objects are notified and since Bob passes the new Burger object as an argument to notifyObservers, they recieve the Burger Bob created.

The Tina class is the receiving end of this pattern. Tina doesn’t know about Bob or any other Observable. She only acts as a receiver for all Observables.

class Tina : Observer{

    val name = "Tina"

    override fun update(o: Observable?, arg: Any?) {
        when (o){
            is Bob -> {
                if (arg is Burger){
                    println("$name is serving the ${arg.name} cooked by ${o.name}")
                }
            }
            else -> println(o?.javaClass.toString())
        }
    }
}

Since Observer is an interface, Tina is forced to implement the update method. The update method has two parameters. The first one is the Observable that is being updated. The other argument is any additional information the Observable passed when calling notifyObservers().

Kotlin distinguishes between nullable and non-null types but Java does not. Anytime we choose to implement Java interfaces or extend abstract classes found in Java, we have to choose if we want null safety or not. There is no way for the Kotlin compiler to know.

In Tina’s case, we have chosen to declare both o and arg as nullable types by adding the question mark (?) after their types. By doing so, we are choosing to accept the null safety offered by the kotlin compiler. We are free to choose otherwise and disregard the null safety, provided we are reasonably sure the types are not going to be null. For example, when I use the Spring framework in Kotlin, I rarely use the null safety because I am usually correct that I am not going to get null from a Spring method.

In this case, I felt it’s better to use the null safety. Observable and Observer are older classes, and we don’t know for sure what may get passed in as parameters to update. Inside of the implementation of update, we have to cast our parameters to the types we need. We can use is operator combined with the when function (see casting). We check if o is Bob and if arg is Burger. When they are, we print out that a Burger is getting served.

There is one final piece to this example. Although Bob and Tina can now work together thanks to Observable and Observer, they need to know about each other. Since Bob extends Observable, he has an addObserver() method that let’s us pass in an instance of Observer.

fun main(args : Array<String>){
    val bob = Bob()
    //Provide Bob and instance of Tina
    bob.addObserver(Tina())

    bob.cookBurger("It takes Bun to Know Bun Burger")
}

Going forward, whenever Bob calls cookBurger, Tina will get notified and serve it.

Putting it Together

Here is the complete program with its output.

package ch4.observer

import java.util.*

class Burger(val name: String)

class Bob : Observable() {

    val name = "Bob"

    fun cookBurger(name : String){
        var burger = Burger(name)

        //Call setChanges() prior to calling notifyObservers()
        setChanged() //Inherited from Observable()
        notifyObservers(burger) //Inherited from Observable()
    }
}

class Tina : Observer{

    val name = "Tina"

    override fun update(o: Observable?, arg: Any?) {
        when (o){
            is Bob -> {
                if (arg is Burger){
                    println("$name is serving the ${arg.name} cooked by ${o.name}")
                }
            }
            else -> println(o?.javaClass.toString())
        }
    }
}

fun main(args : Array<String>){
    val bob = Bob()
    bob.addObserver(Tina())

    bob.cookBurger("It takes Bun to Know Bun Burger")
}

Output

Tina is serving the It takes Bun to Know Bun Burger burger cooked by Bob

Kotlin Abstract Classes

Abstract classes provide developers a place to provide an abstraction point while still being able to include common functionality. In a manner of speaking, an abstract class can be thought of as an unfinished class. It depends on subclasses to finish the class by defining the final behavior of the class. Since abstract classes serve as base classes for concrete classes, we can use them for polymorphism purposes.

Let’s consider a problem that uses abstract classes. We have two cooks. One cook is Bob and he makes burgers. The other cook is Jimmy and he makes pizza. Both cooks have names and own their own restaurants. They also cook food. So in this sense, they both have a lot in common. Although both cooks have the same behavior, cook(), they both cook different things. Bob cooks burgers while Jimmy cooks pizza.

We don’t want to define two classes that are almost completely the same. That would be a really bad practice because then a change in both classes would need to get updated in both places. We also would not be able to define methods that could use both classes without function overloading. In other words, our code would become highly coupled to the implementation of each cook instead of being able to use both cooks generally.

Abstract Class

Here is our Cook class that defines properties and behaviors for both Bob and Jimmy.

abstract class Cook(val name : String, val resturant : String){

    /**
     * This method doesn't have a body.
     * Child classes must define the cook() method
     * or they too must be abstract
     */
    abstract fun cook() : String

    override fun toString(): String {
        return this.name
    }
}

Classes are made abstract in Kotlin by adding the abstract keyword in front of the class keyword. We will never be able to create an instance of the Cook class due to it being marked abstract. Since our cooks cook different meals, we leave the cook method undefined by marking it as abstract as well. Abstract methods are open by default in Kotlin since they have to be overridden by definition. Since we have an abstract cook() method in Cook, we are forcing all subclasses to define this behavior.

Bob

Bob is a Cook so it makes sense that he subclasses Cook. By extending Cook, we are saying that Bob cooks. However, the Cook class doesn’t say what he cooks or how he cooks. We need Bob to extend Cook and define the cook() method.

class Bob : Cook("Bob Belcher", "Bob's Burgers") {

    override fun cook(): String {
        return "Chorizo Your Own Adventure Burger"
    }
}

Since Bob is a cook, he has a name and a restaurant. He not only cooks, but we now know how Bob cooks. Since Bob is a child class of Cook, he can be assigned to any Cook variable.

Jimmy

Jimmy is similar to Bob but he cooks pizzas.

class Jimmy : Cook("Jimmy Pesto", "Petso's Pizzeria"){
    override fun cook(): String {
        return "Boring Pizza"
    }
}

Using Abstract Classes

Now that we have Cook, Bob, and Jimmy defined, we are free to use them in our program. Let’s write a function that takes a Cook, says hello, and tells us what they cook.

fun sayHello(c : Cook){
    println("Hello! My name is ${c.name} and I cook ${c.cook()}")
}

Since Cook has a name property and a cook() method, the compiler knows that its safe to call cook() on any cook. Which version of the cook() method gets called depends on the runtime type of Cook. Regardless of who is the cook, the program will still work properly.

The sayHello function is said to be loosely coupled to the Cook class. Although we can only actually make Bob or Jimmy objects, the Cook class provides a degree of indirection for developer purposes. If we add other cooks, later on, the sayHello function can utilize those objects as well because they are all members of a common supertype.

Putting it Together

Use abstract classes when

  • You need an abstraction point
  • You have one or more child classes that have common behavior and properties
  • You need to declare behavior but need to define it in child classes

Here is an example program that ties everything together

package ch4.abstractclasses

abstract class Cook(val name : String, val resturant : String){

    /**
     * This method doesn't have a body.
     * Child classes must define the cook() method
     * or they too must be abstract
     */
    abstract fun cook() : String

    override fun toString(): String {
        return this.name
    }
}

class Bob : Cook("Bob Belcher", "Bob's Burgers") {

    override fun cook(): String {
        return "Chorizo Your Own Adventure Burger"
    }
}

class Jimmy : Cook("Jimmy Pesto", "Petso's Pizzeria"){
    override fun cook(): String {
        return "Boring Pizza"
    }
}

fun sayHello(c : Cook){
    println("Hello! My name is ${c.name} and I cook ${c.cook()}")
}

fun main(args : Array<String>){
    val bob = Bob()
    val jimmy = Jimmy()

    sayHello(bob)
    sayHello(jimmy)
}

We get this output when run.

Hello! My name is Bob Belcher and I cook Chorizo Your Own Adventure Burger
Hello! My name is Jimmy Pesto and I cook Boring Pizza

Kotlin Koans—Part 11

This portion of the Kotlin Koans tutorial focuses on Object Expressions. Practically speaking, Object Expressions serve the same role as anonymous innner classes in Java. They let us make modifications on a class in one particular case without having to create an entirely new class.

This portion of the tutorial has developers creating a dynamic Comparator class that sorts numbers in descending order.

fun task10(): List {
    val arrayList = arrayListOf(1, 5, 2)
    Collections.sort(arrayList, object: Comparator {
        override fun compare(o1: Int?, o2: Int?): Int {
            return o2?.compareTo(o1 ?: 0) ?: 0
        }
    })
    return arrayList
}

We could have used a lambda in this case, but that would miss the point of what the tutorial is trying to teach. In this code snippet, the second paramter of Collections.sort is an Object Expression that defines a custom Comparator class.

You’ll notice that the definition of compare is full of null safe expressions as indicated the by ? and ?: opeartors. As a side note, I really like how Kotlin has an arrayListOf() function that let’s you create an ArrayList. Sure it does the same thing as Arrays.asList, but again, it’s more concise.

You can view part 10 here

Kotlin Koans—Part 10

This part of the Kotlin Koans tutorial involved extension functions. This is a construct I have never seen in programming before, so it took me a little bit to get an idea of what it is and when to use this feature.

It seems as if the idea here is to add features to a class without have to use inheritence or some sort of delegate object. Here is the Kotlin code.

//This is the class we are adding to
data class RationalNumber(val numerator: Int, val denominator: Int)

//We are adding an r() method to Int which
//returns an instance of RationalNumber
fun Int.r(): RationalNumber = RationalNumber(toInt(), 1)

//We add an r() method to Pair which returns an
//instance of RationalNumber
fun Pair.r(): RationalNumber = RationalNumber(first, second)

The Kotlin documentation has a motivation section that explains the purpose behind extensions. They explain that in many cases in Java, we end up with FileUtils, StringUtils, *Utils classes. In the ideal world, we would want to add features to say the List class directly rather than having a ListUtils class with a bunch of static methods.

We get something like this in JDK8 with default methods that can get placed in an interface. However, that still requires us to extend and interface to add extra methods. Extensions let us work directly on the classes we are already using.

You can click here to see Part 9

Kotlin Koans—Part 9

Java and Kotlin are strongly typed languages. It’s not necessary to cast types when working up an object graph. For example

public void sort(Collection col){
    //todo
}

sort(new ArrayList());
sort(new HashSet());

This is an example of polymorphism in Java. ArrayList and HashSet are both Collections so it’s acceptable to pass either types to the example sort method.

Keep in mind this is not a two way street. This code would not compile.

public void sort(List list){
    //todo
}

Collection col = new ArrayList();
sort(col); //Compile error!
sort((List) col); //OK

Even though col points at an ArrayList and ArrayList implements List, Java forbids you to pass col to sort without a cast. This is because the compiler has no idea that col is pointing at an ArrayList. Keep in mind this is true of Kotlin also.

Although we can get our code to compile with a cast, it’s still dangerous code. Let’s tweak it a little big and have col point at a HashSet instead of ArrayList.

public void sort(List list){
    //todo
}

Collection col = new HashSet();

//Compiles but throws
//ClassCastException
sort((List) col);

Now the code compiles, but it will fail at run time. There is no way to cast HashSet to a List. HashSet does not implement List in anyway so when the code attempts to make the cast, the code will fail. We have to use the instanceof operator to make sure the cast is safe first.

public void sort(List list){
    //todo
}

Collection col = new HashSet();

if (col instanceof List){
    //Now it's safe
    sort((List) col);
}

This code is now safe. It will check if the runtime type of col is a List first. If the object is a List, it will make the cast. Otherwise, the cast will not get made.

Tutorial

This portion of the Kotlin Koans tutorial shows off how Kotlin handles casting compared to Java. Here is the Java code that needs to get rewrote in Kotlin.

public class JavaCode8 extends JavaCode {
    public int eval(Expr expr) {
        if (expr instanceof Num) {
            return ((Num) expr).getValue();
        }
        if (expr instanceof Sum) {
            Sum sum = (Sum) expr;
            return eval(sum.getLeft()) + eval(sum.getRight());
        }
        throw new IllegalArgumentException("Unknown expression");
    }
}

Kotlin has a when keyword that is used for casting. Here is the equivalent Kotlin code.

fun todoTask8(expr: Expr): Int {
    when (expr) {
        is Num -> return expr.value
        is Sum -> return todoTask8(expr.left) + todoTask8(expr.right)
        else -> throw IllegalArgumentException("Unknown expression")
    }
}

As usual, Kotlin is more concise than Java. The when block starts with the when followed by the variable in question. You can have any number of is clauses in this statement followed by the type. The variable is automatically cast to the specified type on the right hand side of the -> operator.

You can click here to see Part 8

Kotlin Koans—Part 7

This portion of the Kotlin Koans showed off a really boss feature of the language: Data Classes. These are special classes whose primary purpose is to hold data.

Here is a Java class that we start with that’s taken directly from the tutorial.

public class Person {
        private final String name;
        private final int age;

        public Person(String name, int age) {
            this.name = name;
            this.age = age;
        }

        public String getName() {
            return name;
        }

        public int getAge() {
            return age;
        }
    }

It’s not a special class. This is a class with a primary constructor, getters/setters and two private variables. It’s also one of my biggest complaints about the Java language. I can do the same thing in Python like this.

class Person:
    def __init__(self, name=None, age=None):
        self.name = name
        self.age = age

Four lines of code in Python. In all fairness to Java, would could just declare name and age to be public variables, but doing so is not only frowned upon, but many Java libraries look for getter/setter method to access a property of a Java bean. Basically speaking, even though we could allow for public access of a Java property, it’s not really practical at this point.

There is a Java library called Lombok that does a lot to solve this problem.

@Data
public class Person {
    private String name;
    private String age;
}

Lombok has been the solution I have used for most of my projects. It’s not perfect however. For example, I can’t use the @Data annotation to make a read only class. That forces me to use a mix of Lombok annotations or define a stereotype annotation. It’s not a huge problem, but it’s still something to think about.

Kotlin data classes take this to a whole other level. Here is the same class in Kotlin.

data class Person(val name: String, val age: Int)

That’s it! One line of code!!! With this single line of code, we get our two properties, it’s getter methods, hashcode, equals, toString() and a constructor. The class is immutable because the variables are declared with the val keyword. We can make the class mutable by using var instead of val. Finally, we aren’t losing our ability to work with existing Java libaries.

I really don’t see how it can get any better than this. I have used data classes countless times when working with ORM libraries such as hibernate. I’d say 95% of these classes are classes that just hold data and map to a table in the database. Although any IDE can generate constructors, getters/setters, equals, and hashcode, and toString, let’s face it, it’s even better to have this built directly into the language itself.

You can click here to see Part 6