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FunctionalReactiveAbout 2 min


Monad pattern based on monad from linear algebra represents the way of chaining operations
together step by step. Binding functions can be described as passing one's output to another's input
basing on the 'same type' contract. Formally, monad consists of a type constructor M and two
bind - that takes monadic object and a function from plain object to monadic value and returns monadic value
return - that takes plain type object and returns this object wrapped in a monadic value.


The Monad pattern provides a way to chain operations together and manage sequencing,
side effects, and exception handling in a consistent manner.

Real-world example

Consider a conveyor belt in a factory: items move from one station to another,
and each station performs a specific task, with the assurance that every task will be carried out,
even if some items are rejected at certain stations.

In plain words

Monad pattern ensures that each operation is executed regardless of the success or failure of previous ones.

Wikipedia says

In functional programming, a monad is a structure that combines program fragments (functions)
and wraps their return values in a type with additional computation. In addition to defining a
wrapping monadic type, monads define two operators: one to wrap a value in the monad type, and
another to compose together functions that output values of the monad type (these are known as
monadic functions). General-purpose languages use monads to reduce boilerplate code needed for
common operations (such as dealing with undefined values or fallible functions, or encapsulating
bookkeeping code). Functional languages use monads to turn complicated sequences of functions into
succinct pipelines that abstract away control flow, and side-effects.

Programmatic Example

Here’s the Monad implementation in Java.

The Validator takes an object, validates it against specified predicates, and collects any
validation errors. The validate method allows you to add validation steps, and the get method
either returns the validated object or throws an IllegalStateException with a list of validation
exceptions if any of the validation steps fail.

public class Validator<T> {
  private final T obj;
  private final List<Throwable> exceptions = new ArrayList<>();

   private Validator(T obj) {
    this.obj = obj;
  public static <T> Validator<T> of(T t) {
    return new Validator<>(Objects.requireNonNull(t));

  public Validator<T> validate(Predicate<? super T> validation, String message) {
    if (!validation.test(obj)) {
      exceptions.add(new IllegalStateException(message));
    return this;

  public <U> Validator<T> validate(
      Function<? super T, ? extends U> projection,
      Predicate<? super U> validation,
      String message
  ) {
    return validate(projection.andThen(validation::test)::apply, message);

  public T get() throws IllegalStateException {
    if (exceptions.isEmpty()) {
      return obj;
    var e = new IllegalStateException();
    throw e;

Next we define an enum Sex.

public enum Sex {

Now we can introduce the User.

public record User(String name, int age, Sex sex, String email) {

And finally, a User object is validated for its name, email, and age using the Validator monad.

public static void main(String[] args) {
        var user = new User("user", 24, Sex.FEMALE, "");, Objects::nonNull, "name is null")
        .validate(User::name, name -> !name.isEmpty(), "name is empty")
        .validate(User::email, email -> !email.contains("@"), "email doesn't contains '@'")
        .validate(User::age, age -> age > 20 && age < 30, "age isn't between...").get()

Class diagram

alt text


Use the Monad in any of the following situations

  • When you want to chain operations easily
  • When you want to apply each function regardless of the result of any of them