Kotlin Koans—Part 23

This portion of the Kotlin Koans tutorial appeared to be a review of the concepts I had been working on throughout the collection section. I had to solve three different problems using the collections API. While doing this, I got to revist the Elivis operator (?:), map, maxBy, sumBy, filter, count, and toSet.

Get Customers Who Ordered Product

This problem focused on filtering.

fun Shop.getCustomersWhoOrderedProduct(product: Product): Set {
    // Return the set of customers who ordered the specified product
    return customers.filter { it.orderedProducts.contains(product) }.toSet()
}

The filter method takes a predicate that returns true or false. In this case, I just used the contains method on orderedProducts. If the product is found in orderedProducts, we get a true, otherwise false. Then there is a toSet() operation to transform the collection to a set.

Get Most Expensive Delived Products

This problem was a little more challenging. I had to go back and review how to use the Elivis operator (TODO: Link).

fun Customer.getMostExpensiveDeliveredProduct(): Product? {
    // Return the most expensive product among all delivered products
    // (use the Order.isDelivered flag)
    return orders.filter { it.isDelivered }.map { it.products.maxBy { it.price } }.maxBy { it?.price ?: 0.0}
}

I started with a filter operation to check if an order was delivered or not since the problem statement required me to find the most expensive delivered product. Then I had to use a map operation which allowed me to traverse all delivered orders. At this point, I could use a maxBy operation and check it.price. This builds up a collection of products that contains the most expensive product on each order.

The next part of the operation is to find the most expensive product of all orders. At this point, I have a collection of products so I just needed another maxBy operation. However it was a little more trickey this time. In this case, there was a possibily that the variable it could be null. It’s nice that Kotlin has compiler checks for this sort of thing because I truthfully didn’t realize that I could be working with null objects here. Thus, I had to use the Elvis operator in this final lambda operation.

Get Number Of Times Product Was Ordered

I had to solve this problem by chaining transformations together again.

fun Shop.getNumberOfTimesProductWasOrdered(product: Product): Int {
    // Return the number of times the given product was ordered.
    // Note: a customer may order the same product for several times.
    return customers.sumBy { it.orders.sumBy { it.products.count { it == product } } }
}

A customer has a one to many relationship with orders, and orders have a one to many relationship with products. I needed two sumBy operations to solve this problem. I began with a sumBy on customers. Inside of the lambda, I did another sumBy operation on orders. Once I was traversing orders, I could do a count operation on products and get a total of how many products matched my predicate.

The it.products.count returns a number that gets fed into it.orders.sumBy. The it.orders.sumBy returns a number that gets fed into customers.sumBy. Once customers.sumBy returns, we have a count of the total number of times the specified product was ordered.

You can click here to see Part 22

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Kotlin Koans—Part 22

More functional programming on the horizon. This portion of Kotlin Koans demonstrated folding. I personally had never tackled a challenge like this so it took me more time to figure it out than the other problems. My job was to go through all customers and the products they ordered and reduce them down to a single set of objects. Here is the Kotlin code.

fun Shop.getSetOfProductsOrderedByEveryCustomer(): Set {
    // Return the set of products ordered by every customer
    return customers.fold(allOrderedProducts, {
        orderedByAll, customer ->
            orderedByAll.intersect(customer.orderedProducts)
    })
}

As usual, I tried to do the same problem in Java for comparison purposes, but I wasn’t able to figure it out! (If you know the solution, please leave it in the comments section!). I’ll have to admit that I am weak in some of the functional programming areas.

You can click here to see Part 21.

Kotlin Koans—Part 21

The Kotlin Koans tutorial continues with more demonstrations about the extensions on collection classes. This portion of the tutorial was a partitioning problem where I had to return the customers that have not had their orders delivered. Here is the code.

fun Shop.getCustomersWithMoreUndeliveredOrdersThanDelivered(): Set {
    // Return customers who have more undelivered orders than delivered
    return customers.partition { it.orders.all { it.isDelivered } }.second.toSet()
}

Kotlin adds a partition method to it’s collection classes. The partition method takes a lambda expression that returns a boolean. Inside of this lambda, I used the all (#TODO Link to All) method on the orders collection. Once again, I am returning a boolean value.

Now for the coolest part. Kotlin has a pair class that has a first and second method. Since I need the orders that are not delievered, I use the second property on the Pair class. At this point, second is holding a collection of Customers whose orders are not delivered. Finally, I can use the toSet (#TODO Link) method to transform the collection into a set.

Like the last few portions of this tutorial, I decided to compare the Kotlin code to the Java 8 code. Here is what I came up with.

public static Set getCustomersWithMoreUndeliveredOrdersThanDelivered(Shop shop){
    return new HashSet(shop.getCustomers()
            .stream()
            .collect(Collectors.partitioningBy((Customer c) -> c.getOrders().stream().allMatch(Order::isDelivered)))
            .get(false));
}

You can click here to see Part 20.

Kotlin Koans—Part 20

Grouping objects by a property and storing them into a map is a challenge that all developers have faced at some point in time. For example, you may have a collection of Customers and you wish to find out which Customers live in each city. Basically, you want a map where City is the key and a Collection of Customers associated with that City is the value.

This was exactly the problem that Kotlin Koans tutorial had me do.

fun Shop.groupCustomersByCity(): Map {
    // Return a map of the customers living in each city
    return customers.groupBy { it.city }
}

I was able to arrange all of the Customers by city with just one line of Kotlin code. The related Java code wasn’t that difficult either, but I did have to search for the solution since it wasn’t quite as clear as the Kotlin approach.

public static Map groupCustomersByCity(Shop shop){
    return shop.getCustomers().stream().collect(Collectors.groupingBy(Customer::getCity));
}

What helped me with the Kotlin approach was that since the groupBy method was direclty on the Collection object, my IDE was able to supply me with the groupBy method. That’s not the case with the Java approach since it’s using a static method on the Collectors class. It also didn’t occur to me to use the collect method on the Stream object either. I was looking for something that said group in it.

You can click here to see Part 19.

Kotlin Koans—Part 19

This section of the Kotlin Koans tutorial continued onward with Kotlin’s collection API enhancement. The challenge in this section use to total the price of all products a customer purchased. Here is the code

fun Customer.getTotalOrderPrice(): Double {
    // Return the sum of prices of all products that a customer has ordered.
    // Note: a customer may order the same product for several times.
    return orders.sumByDouble { it.products.sumByDouble { it.price } }
}

The collection API in Kotlin has a sumByDouble method, which takes a lambda expression. The lambda let’s developers chain function calls. In this case, each Customer had a collection of Products in each Order. To get the price of all Products ordered, I needed the sum of the price of all products in a order. This was easy enough to do because I just made a nested call to sumByDouble on it.products and then told it to sum on it.price.

Here is Java code that solves the same problem.

public static double getTotalOrderPrice(Customer customer){
    return customer
            .getOrders()
            .stream()
            .mapToDouble(
                    order -> order.getProducts()
                                    .stream()
                                    .mapToDouble(Product::getPrice)
                            .sum())
            .sum();
}

You can click here to see Part 18

Kotlin Koans—Part 12

The last part of the Kotlin Koans tutorial had me use Object Expressions to sort an ArrayList. I observed that this could have been done with a lambda expression and I was correct.

This portion of the tutorial discusses implementing an interface with one abstract method. Kotlin calls such interfaces a SAM interface (Single Abstract Method). Whenever a developer is working with a SAM interface, they are free to use a lambda expression rather than an Object Expression.

Here is the Kotlin code that uses a lambda expression

fun task11(): List {
    val arrayList = arrayListOf(1, 5, 2)
    Collections.sort(arrayList, { x, y -> y.compareTo(x) })
    return arrayList
}

I should point out that Java 8 supports lambda expressions now also. Java calls SAM interfaces Functional interfaces. You can even add a @Functional annotation to such interfaces in Java.

I don’t see any huge advantage to Kotlin lambdas over Java ones at this point. Of course, Android developers may appreciate Kotlin’s lambda support.

You can view part 11 here.

Kotlin Koans—Part 5

Many modern programming lanugages have support for functional programming. I remember when Java got support for functional programming in JDK8. I have to say it was awesome to finally get support for functional programming.

Of course, Java has supported functional programming to a certain degree for a while now through anonymous inner classes. The syntax was verbose…

public class Window extends JFrame {
    
    public Window(){
        JButton jButton = new JButton("Button");
        jButton.addActionListener(new ActionListener() {
            @Override
            public void actionPerformed(ActionEvent e) {
                System.out.println("Clicked");
            }
        });
    }
}

Java 8 simplified this mess when it officially supported functional programming.

public class Window extends JFrame {

    public Window(){
        JButton jButton = new JButton("Button");
        jButton.addActionListener(e -> System.out.println("Clicked"));
    }
}

Readers can see that the above code is far more consise than the previous example so many Java developers, including myself, were greatful for the change. Android developers weren’t so lucky and unless things have changes, Android developers still have to live with anonymous inner class syntax.

That is until Kotlin came along and is now supported for Android. In this portion of the Kotlin Koans tutorial, I had to rewrite this Java code into Kotlin.

public class JavaCode4 extends JavaCode {
    public boolean task4(Collection collection) {
        return Iterables.any(collection, new Predicate() {
            @Override
            public boolean apply(Integer element) {
                return element % 42 == 0;
            }
        });
    }
}

Of course, JDK 8 developers get the Stream API and lambda syntax, while Android developers were out of luck. Here is the equivalent Kotlin code.

fun task4(collection: Collection): Boolean{
    return collection.any { element -> element % 42 == 0 }
}

You can click here to see Part 4