In this article, we will learn how to use Function functional interface. Let’s get started.

Table of contents

Introduction to Function functional interface

  1. Function interface

    Function is a functional interface with two type parameters T and R. Its functional method called apply(), takes an argument of type T and returns an object of type R. Functions are ideal for converting an object of type T to one of type R.

     public interface Function<T, R> {
         R apply(T t);

    For example:

     Function<String, Integer> func = str -> Integer.parseInt(str);
     // pass function interface to a method
     public static <T, R> R transform(T t, Function<T, R> func) {
         return func.apply(t);
  2. BiFunction interface

    Continuously, we will go through BiFunction interface with two type parameters for input types in addition to the output type parameter.

     public interface BiFunction<T, U, R> {
         R apply(T, U);

    For example:

     BiFunction<String, String, String> func = (s1, s2) -> {
         s3 = s1 + s2;   

Chaining with Function interface

In order to implement chaining with Function interface, we will find something out about some default methods.

// andThen() method applies an additional operation after the operation specified by the apply() method
// completes.
default <V> Function<T, V> andThen(Function<? super R, ? extends V> after);

// compose() method applies a preliminary operation before the operation specified by the apply() method
default <V> Function<V, R> compose(Function<? super V, ? extends T> before);

For example:

Chaining with BiFunction interface

In BiFunction interface, it is only defined andThen() default method for chaining expressions.

default <V> BiFunction<T,U,V> andThen(Function<? super R,? extends V> after)

For example:

High-order function

Just like classes are first-class citizens in object-oriented programming, functions are first-class citizens in functional programming. In this context, a function becomes a high-order function when it takes a function as its input, or argument. It returns a function as its output, or both.

We can compare high-order functions with one of the most popular design patterns in OOP, strategy pattern. This pattern allows us to encapsulate the behavior that varies in a supertype, making different behaviors, the subclasses, interchangeable. In Java, this pattern is usually implemented using an interface, creating different implementations for different behaviors.

For example, we can have an interface, RewardPointsGenerator, with a method to calculate their reward from a customer order.

Order processOrder(Order order, RewardPointsGenerator rewardPointGenerator) {
    // ...
    RewardPoints rp = rewardPointGenerator.calculate(order);
    // ...

The method that processOrder() can take one of its argument as an implementation of this interface. This way, when calling processOrder(), we can pass different implementations to calculate the reward in different ways.

RewardPointsGenerator totalBaseRP = order -> { /* ... */ }
RewardPointsGenerator numProductsBaseRP = order -> { /* ... */ }

Order processOrder1 = processOrder(order, totalBaseRP);
Order processOrder2 = processOrder(order, numProductsBaseRP);

We can see the processOrder() as a high-order function, accepting a function with the algorithm to calculate the reward points as one of its inputs. But we do not need RewardPointsGenerator. We can use the function interface to implement a function from order to RewardPoints in this way. And to avoid the clutter of a lambda expression with a body, we can move the code to a method and use a method reference.

Order processOrder1 = processOrder(order, this::totalBaseRewardPoints);
Order processOrder2 = processOrder(order, this::numProductsBaseRewardPoints);

In any case, object oriented, or functional programming, having simple units of code that are easy to read and test is a good practice, and that’s exactly what high-order functions can be small, concise units of code that are easy to test and make the core more readable.

This benefit comes from the design process, in particular, from the ability to abstract behavior that can be implemented with high-order functions and compose these high-order functions. This can also give us the ability to reuse the functions we create.

Both object-oriented and functional programming seek the same goals, in this case, abstraction, composition, and reusability, but they do it in a different way. Object-oriented programming uses classes as its main tool. We can compose new classes from existing ones. We can abstract behavior into classes for reusing.

In functional programming, it’s the same, but using functions as the main tool. However, with high-order functions, functional programming tends to use a more declarative style for programming.

List<Integer> filteredList = new ArrayList<>();
for (int n : listOfNumbers) {
    if (n % 3 == 0) {

So instead of having a loop where we explicitly tell how to iterate and filter a list, in functional programming, we have the below piece of code.

List<Integer> filteredList =
                                          .filter(n -> n % 3 == 0)

The filter function does not expose how it works. It simply asks for another function to declare the intention of what we want to do.

// use point-free style and method reference
Predicate<Integer> divisibleBy3 = n -> n % 3 == 0;
List<Integer> filteredList =

There’s a style of programming called point-free programming, that is about passing a named function as an argument to avoid writing an inline lambda expression and its parameters. We can also use method reference. The idea of using point-free style is to improve the clarity and readability of the code, and by chaining two or more of these high-order functions, we can create pipelines to transform collections.

Source code

In order to see how Predicate functional interface works, we can reference to Function functional interface.

Some useful examples for applying Function and BiFunction interface

Assuming that we have a list of Student that we get from database, our tasks are:

  • search Student instances that have the same name.

      BiFunction<String, List<Student>, List<Student>> searchByName = (name, students) -> {

                  .filter(str -> str.equals(name))
  • get Student instance that has the maximum score.

      Function<List<Student>, List<Student>> sortedByScore = students -> {

                  .sorted((x, y) -> y.getAge() > x.getAge())
      Function<List<Student>, Optional<Student>> first = student ->;
      Function<List<Student>, Optional<Student>> findMaxScore = first.compose(sortedByScore);

When to use

  • It is used in the map operation of the Stream API.

  • When we want to convert some kind of objects.

Benefits and Drawbacks

  1. Benefits

    • Using Function interface makes our code DRY.

    • easy to understand what it does, and maintain.

Wrapping up

  • BiFunction interface only offers andThen() method, not compose() method, because compose() method will return single result, then it is not accepted as argument of another BiFunction with two input parameters.

  • Some specialization of Function interface that used to convert from primitive types such as IntFunction, LongFunction, DoubleFunction.

      public interface IntFunction<R> {
          R apply(int value);
      public interface LongFunction<R> {
          R apply(long value);
      public interface DoubleFunction<R> {
          R apply(double value);
  • Some specialization of Function interface that used to convert to primitive types such as ToIntFunction, ToLongFunction, ToDoubleFunction.

      public interface ToIntFunction<T> {
          int applyAsInt(T value);
      public interface LongFunction<T> {
          long applyAsLong(T value);
      public interface DoubleFunction<T> {
          double applyAsDouble(T value);
  • Some non-generic specialization of Function interface such as DoubleToIntFunction, DoubleToLongFunction, IntToDoubleFunction, IntToLongFunction, LongToDoubleFunction, LongToIntFunction.


Functional Interfaces in Java book