The next Koan looks at how Kotlin handles nulls, and it does it wonderfully; Null is explicitly opt-in. For example, in C# you can assign null to a string variable but in Kotlin unless you say you want to support nulls, which you do by adding a trailing question mark to the class, you cannot.

Their example in this Koan is a nice example:

if (q != null) q.length      // you have to check to dereference
val i: Int? = q?.length      // null
val j: Int = q?.length ?: 0  // 0

}

Let us dig into the Koan, where we get given the following Java code:

PersonalInfo personalInfo = client.getPersonalInfo();
if (personalInfo == null) return;

String email = personalInfo.getEmail();
if (email == null) return;

mailer.sendMessage(email, message);

}

and we need are going to rewrite it using the Nullable language features of Kotlin, which looks like:

mailer.sendMessage(email, message)

}

The big changes from Java:

1. The @NotNull attribute for mailer is no longer needed
2. The @Null attribute for the other parameters becomes the question mark
3. We do not need to pre-check client before calling the parameter, as you can use the null safe operator ?. to ensure you only check before we call the method.
4. Unfortunately, the null safe operator in Kotlin doesn’t support calling methods on null objects as C# currently does with its Elvis operator

This post is one in a series of stuff formally trained programmers know – the rest of the series can be found in the series index.

In this post, we will look at two related and simple data structures, the Stack and the Queue. The stack is a structure which can be implemented with either an Array or Linked List.

An important term for understanding a stack is that it is LIFO, last-in-first-out, system; namely, the last item you add (or push or bury) is the first item you take out when you retrieve an item (or peek or unbury).

Let’s have a look at what a stack would look like:

In this, we added 1, 2, 3, 4, and then 5 and when we read from the stack we read in the reverse order.

#Implementations

• Java has a Stack
• C# has a Stack

Next is the queue, which is very similar to the stack, except where the stack was LIFO; a queue is FIFO, first-in-first-out; so if we put in 1, 2, 3, 4, & 5 into the queue, then we would read them in the same order, i.e. 1, 2, 3, 4, 5.

Implementations

C# has a queue implementation and the JavaScript array can act as a queue, when you use unshift to add to the beginning of the array (also known as the head) and pop to remove from the end of the array (also known as the tail).

WOW! Data Classes are awesome! I really like a lot of how classes are handled in Kotlin, but Data Classes are the pinnacle of that work. The effort for this Koan is to convert this Java class to Kotlin:

public static 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;
    }
}

}

and what does that look like in Kotlin?

Yup, a single line. The data annotation adds a number of important functions (like ToString and copy). We then declare the class with a constructor which takes two parameters which both become properties.

Another important aspect I learnt with this one is that Kotlin has both a val and var keyword for variables. We have seen var already and val is for read-only variables.

The purpose of this lesson is to show off string templating and the Koan starts with some interesting examples

fun example3(c: Boolean, x: Int, y: Int) = “Any expression can be used: ${if (c) x else y}”

If you are used to string templates from C# and JavaScript this should be fairly simple to understand.

The fourth example is interesting

This brought up something I’ve never heard of, raw strings. Raw strings seem to be the Python way of saying a Verbatim string… which I didn’t know was the official term.

The actual Koan here is about converting this fun getPattern() = """\d{2}\.\d{2}\.\d{4}""" to a different regular expression, using a string template:

It isn’t that interesting and really, if you don’t know regular expressions this could be tougher than it needs be.

So following C#, Kotlin has Lambda support with the change if => becoming -> and the Koan starts with some nice examples at the start:

val sum = { x: Int, y: Int -> x + y }
val square: (Int) -> Int = { x -> x * x }

sum(1, square(2)) == 5

}

Basically, though, the code that needs to be done is to check a collection if all items are even, which is easily done with:

Previously we covered Named Arguments and this is a small continuation from it, we start with a simple function fun foo(name: String): String = todoTask3() and we need to have it call a single Java function and to provide it with default values which ultimately looks like this:

On to our third exercise and definitely, the difficulty curve has lowered again (or should it be steep) as we have a simple lesson - how to use named arguments.

Not only is an example for it provided for how named arguments work:

We also get an example of default values for arguments

The problem we need to solve itself is simple too,

Print out the collection contents surrounded by curly braces using the library function ‘joinToString’. Specify only ‘prefix’ and ‘postfix’ arguments.

Which has this answer:

Not much to add to this lesson unfortunately.

The second Koan is meant as an exercise of the IDE and is targeted at those moving from Java, as such this was a mixed bag for me.

The goal is to get a Kotlin version of Java code by letting the IDE do the conversion, but I decided to tackle it myself.

Initially, I thought I needed to do the entire file and not just the task function. So, what does the entire code look like when changed?

package i_introduction._1_Java_To_Kotlin_Converter;

import util.JavaCode;

import java.util.Collection;
import java.util.Iterator;

public class JavaCode1 extends JavaCode {
    public String task1(Collection<Integer> collection) {
        StringBuilder sb = new StringBuilder();
        sb.append("{");
        Iterator<Integer> iterator = collection.iterator();
        while (iterator.hasNext()) {
            Integer element = iterator.next();
            sb.append(element);
            if (iterator.hasNext()) {
                sb.append(", ");
            }
        }
        sb.append("}");
        return sb.toString();
    }
}

package i_introduction._1_Java_To_Kotlin_Converter;

import util.JavaCode;

import kotlin.collections.Collection;

 class JavaCode1 : JavaCode() {
    fun task1(collection : Collection<Int>) : String {
        val sb = StringBuilder()
        sb.append("{")
        val iterator = collection.iterator()
        while (iterator.hasNext()) {
            val element = iterator.next()
            sb.append(element)
            if (iterator.hasNext()) {
                sb.append(", ")
            }
        }
        sb.append("}")
        return sb.toString()
    }
 }

The first thing you’ll notice is that the java.util.Collection is gone since Kotlin has its’ own implementation and is imported by default.

Next is the code’s lack of Visibility Modifiers. This is because everything is public by default. In addition to public there are protected, private and internal which work the same .NETs modifiers.

The next change is the variables, you don’t need to define the type before the variable… you just define val for read-only variables or var for mutable variables. This is similar to C#s var keyword.

The final change is the lack of semicolons. This doesn’t mean Kotlin doesn’t have them, it means they are optional. You can add them as if it was Java or C# with no issue, it is you don’t need them unless you are doing something confusing for the compiler.

This post is one in a series of stuff formally trained programmers know – the rest of the series can be found in the series index.

Building off of the Binary Search Tree, we get the red/black tree which aims to solve the problem that a BST can become unbalanced.

The short version of a red/black tree is that is a BST with a set of rules that help us keep it performing well.

Thinking back to the BST, when we are doing the inserts and deletes at some point we need to rebalance the tree to ensure we keep that sweet O(log n) performance for searching. When is the right time to do that rebalancing?

A red/black tree extends a BST by adding one bit of information to each node; for those keeping track, our node now has the data, a key and a flag.

The flag is either red/black and there are 7 rules a BST (there are 5 official ones that relate to the colours, the first 5 below, but there are two more for the BST itself):

1. Each node is either red or black
2. The root node is black
3. All leaves are black. These leaves can be the null points off of a node or they can be explicit nodes.
4. A red node can only have black children
5. Any path from a node to the leaves contains the same number of black nodes
6. New nodes added are always Red.
7. If the depth of a path is more than twice that of the shorted path we need to do a rotation.

So with these rules, insert & delete get more complex because you need to check these rules and, if the rules do not work you start to correct the issue. What is great with this is that because of the rules you become really efficient at correcting the problems.

So let’s look at a really simple BST:

Next, let’s make it a red/black tree following our rules above. I am also going to add the leave nodes in this image to help explain it but will take them out the remaining ones.

Note:

• that from the root node you need to go through 1 black node to reach a leaf node regardless of path.
• All red nodes only have black children.
• A black node can have black children.

Now we are going to add a node with value 11. It is added in the correct place and as a red node.

However 9 is red and has a red child, so we need to trigger a repaint of it to black. That causes a new issue, that from the root node to the leaves you may go through 1 black node by going left or 2 black nodes by going right, so we need to paint the parent of 9 (i.e. 7) to red. Lastly, since 7 is now red, 6 must be repainted to black. Finally, we have a correct red/black tree again.

Lastly let us add 10, which goes under 11. Immediately we note that the length from 5 to the leaf of 10 is 4 steps, while the shortest path (the left side) is 2. We know we need to do a rotation.

The rotation is easy, we take the child of the longer side (i.e. 7) and make it root and make the original root (i.e. 5) a child of it. Since 7 has two children already (5 and 9), it’s original child 6 moves to under 5. Next, we just trigger a repaint, starting with the fact 7 needs to be black and you end up with the following:

This might seem really expensive to do, but since you are just changing pointers and only a few the performance of the insert becomes also O(log n).

Implementations

Unfortunately, neither Java, .NET nor JavaScript has out of the box implementations but there are plenty of ones available if you search for it.

So let’s start with line one: package i_introduction._0_Hello_World

In Kotlin package is just the same as a package in Java or Namespaces in .NET. There is no link between package name and the filesystem.

Next up is imports: import util.TODO import util.doc0

Imports are the same as import in Java and Using in C#. Kotlin does import a number of packages by default:

• kotlin.*
• kotlin.annotation.*
• kotlin.collections.*
• kotlin.comparisons.* (since 1.1)
• kotlin.io.*
• kotlin.ranges.*
• kotlin.sequences.*
• kotlin.text.*

Next up is our first function defination fun todoTask0(): Nothing = ...

We use the fun keyword to state it is a function, followed by the function name todoTask0 and the parameters… in this case, that is empty.

The function returns Nothing though that isn’t specifically required as the compiler can infer the return type.

This is a single statement function so it ends with an equal sign.

The next function is a little different fun task0(): String { return todoTask0() }

The second function returns a String and is not a single statement function.

So how do we solve this Koan?