In this article by Ivan Nikolov, author of the book Scala Design Patterns, explains in the world of computer programming, there are multiple different ways to create a solution that does something. However, some might contemplate whether there is a correct way of achieving a specific task. The answer is yes; there is always a right way, but in software development, there are usually multiple ways to do achieve a task. Some factors exist, which guide the programmer to the right solution, and depending on them, people tend to get the expected result. These factors could define many things—the actual language being used, algorithm, type of executable produced, output format, and the code structure. The language is already chosen for us—Scala. There are, however, a number of ways to use Scala, and we will be focusing on them—the design patterns.

In this article, we will explain what design patterns are and why they exist. We will go through the different types of design patterns that are out there. This aims to provide useful examples to aid you in the learning process, and being able to run them easily is key. Hence, some points on how to set up a development environment properly will be given here. The top-level topics we will go through are as follows:

What is a design pattern and why do they exist?
The main types of design patterns and their features
Choosing the right design pattern
Setting up a development environment in real life

The last point doesn't have to do much with design patterns. However, it is always a good idea to build projects properly, as this makes it much easier to work in future.

(For more resources related to this topic, see here.)

Design patterns

Before delving into the Scala design patterns, we have to explain what they actually are, why they exist, and why it is worth being familiar with them.

Software is a broad subject, and there are innumerable examples of things people can do with it. At first glance, most of the things are completely different—games, websites, mobile phone applications, and specialized systems for different industries. There are, however, many similarities in how software is built. Many times, people have to deal with similar issues no matter the type of software they create. For example, computer games as well as websites might need to access a database. And throughout time, by experience, developers learn how structuring their code differs for various tasks that they perform.

A formal definition for design patterns would help you understand where we are actually trying to get using good practices in building software.

The formal definition for design patterns

A design pattern is a reusable solution to a recurring problem in a software design. It is not a finished piece of code, but a template, which helps solving the particular problem or family of problems.

Design patterns are best practices to which the software community has arrived over a period of time. They are supposed to help write efficient, readable, testable, and easily extendable code. In some cases, they can be a result of a programming language not being expressive enough to elegantly achieve a goal. This means that more feature-rich languages might not even need a design pattern, while others still do. Scala is one of those rich languages, and in some cases, it makes use of a design pattern that is obsolete or simpler.

The lack or existence of a certain functionality within a programming language also makes it able to implement additional design patterns that others cannot. The opposite is also valid—it might not be able to implement things that others can.

Scala and design patterns

Scala is a hybrid language, which combines features from object-oriented and functional languages. This not only allows it to keep some of the well-known object-oriented design patterns relevant, but it also provides various other ways of exploiting its features to write code, which is clean, efficient, testable, and extendable all at the same time. The hybrid nature of the language also makes some of the traditional object-oriented design patterns obsolete, or possible, using other cleaner techniques.

The need for design patterns and their benefits

Everybody needs design patterns and should look into some before writing code. As we mentioned earlier, they help writing efficient, readable, extendable, and testable code. All these features are really important to companies in the industry.

Even though in some cases it is preferred to quickly write a prototype and get it out, usually the case is that a piece of software is supposed to evolve. Maybe you will have experience of extending some badly written code, but regardless, it is a challenging task and takes really long, and sometimes it feels that rewriting it would be easier. Moreover, this makes introducing bugs into the system much more likely.

Code readability is also something that should be appreciated. Of course, one could use a design pattern and still have their code hard to read, but generally, design patterns help. Big systems are usually worked on by many people, and everyone should be able to understand what exactly is going on. Also, people who join a team are able to integrate much easily and quickly if they work on some well-written piece of software.

Testability is something that prevents developers from introducing bugs when writing or extending code. In some cases, code could be created so badly that it is not even testable. Design patterns are supposed to eliminate these problems as well.

While efficiency is many times connected to algorithms, design patterns could also affect it. A simple example could be an object, which takes a long time to instantiate and instances are used in many places in an application, but could be made singleton instead.

Design pattern categories

The fact that software development is an extremely broad topic leads to a number of things that can be done with programming. Everything is different and this leads to various requirements about the qualities of programs. All these facts have caused many different design patterns to be invented. This is further contributed to by the existence of various programming languages with different features and levels of expressiveness.

This article focuses on the design patterns from the point of view of Scala. As we already mentioned previously, Scala is a hybrid language. This leads us to a few famous design patterns that are not needed anymore—one example is the null object design pattern, which can simply be replaced by Scala's Option. Other design patterns become possible using different approaches—the decorator design pattern can be implemented using stackable traits. Finally, some new design patterns become available, which are applicable specifically to the Scala programming language —the cake design pattern, pimp my library, and so on. We will focus on all of these and make it clear where the richness of Scala helps us to make our code even cleaner and simpler.

Even if there are many different design patterns, they can all be grouped in a few main groups:

Creational
Structural
Behavioral
Functional
Scala-specific design patterns

Some of the design patterns that are specific to Scala can be assigned to the previous groups. They can either be additional or replacements of the already existing ones. They are typical to Scala and take advantage of some advanced language features or simply features not available in other languages.

The first three groups contain the famous Gang of Four design patterns. Every design pattern article covers them and so will we. The rest, even if they can be assigned to one of the first three groups, will be specific to Scala and functional programming languages. In the next few subsections, we will explain the main characteristics of these groups and briefly present the actual design patterns that fall under them.

Creational design patterns

The creational design patterns deal with object creation mechanisms. Their purpose is to create objects in a way that is suitable to the current situation, which could lead to unnecessary complexity and the need of extra knowledge if they were not there. The main ideas behind the creational design patterns are as follows:

Knowledge encapsulation about the concrete classes
Hiding details about the actual creation and how objects are combined

We will be focusing on the following creational design patterns in this article:

The abstract factory pattern
The factory method pattern
The lazy initialization pattern
The singleton pattern
The object pool pattern
The builder pattern
The prototype pattern

The following few sections give a brief definition of what these patterns are.

The abstract factory design pattern

This is used to encapsulate a group of individual factories that have a common theme. When used, the developer creates a specific implementation of the abstract factory and uses its methods in the same way as in the factory design pattern to create objects. It can be thought of as another layer of abstraction that helps instantiating classes.

The factory method design pattern

This design pattern deals with creation of objects without explicitly specifying the actual class that the instance will have—it could be something that is decided at runtime based on many factors. Some of these factors can include operating systems, different data types, or input parameters. It gives developers the peace of mind of just calling a method rather than invoking a concrete constructor.

The lazy initialization design pattern

This pattern is an approach to delay the creation of an object or the evaluation of a value until the first time it is needed. It is much more simplified in Scala than it is in an object-oriented language as Java.

The singleton design pattern

This design pattern restricts the creation of a specific class just to one object. If more than one class in the application tries to use such an instance, then this same instance is returned for everyone. This is another design pattern that with the use of basic Scala features can be easily achieved.

The object pool design pattern

This pattern uses a pool of objects that are already instantiated and ready for use. Whenever someone requires an object from the pool, it is returned, and after the user is finished with it, it puts it back into the pool manually or automatically. A common use for pools are database connections, which generally are expensive to create; hence, they are created once and then served to the application on request.

The builder design pattern

The builder design pattern is extremely useful for objects with many possible constructor parameters, which would otherwise require developers to create many overrides for the different scenarios an object could be created in. This is different to the factory design pattern, which aims to enable polymorphism. Many of the modern libraries today employ this design pattern. As we will see later, Scala can achieve this pattern really easily.

The prototype design pattern

This design pattern allows object creation using a clone() method from an already created instance. It can be used in cases when a specific resource is expensive to create or when the abstract factory pattern is not desired.

Structural design patterns

Structural design patterns exist in order to help establish the relationships between different entities in order to form larger structures. They define how each component should be structured so that it has very flexible interconnecting modules that can work together in a larger system. The main features of structural design patterns include the following:

The use of composition to combine the implementations of multiple objects
Help build a large system made of various components by maintaining a high level of flexibility

In this article, we will focus on the following structural design patterns:

Adapter
ge
Composite
FacDecorator
Bridade
Flyweight
Proxy

The next subsections will put some light on what these patterns are about.

The adapter design pattern

The adapter design pattern allows the interface of an existing class to be used from another interface. Imagine that there is a client who expects your class to expose a doWork() method. You might have the implementation ready in another class but the method is called differently and is incompatible. It might require extra parameters too. This could also be a library that the developer doesn't have access to for modifications. This is where the adapter can help by wrapping the functionality and exposing the required methods. The adapter is useful for integrating the existing components. In Scala, the adapter design pattern can be easily achieved using implicit classes.

The decorator design pattern

Decorators are a flexible alternative to sub classing. They allow developers to extend the functionality of an object without affecting other instances of the same class. This is achieved by wrapping an object of the extended class into one that extends the same class and overrides the methods whose functionality is supposed to be changed. Decorators in Scala can be built much easily using another design pattern called stackable traits.

The bridge design pattern

The purpose of the bridge design pattern is to decouple an abstraction from its implementation so that the two can vary independently.

It is useful when the class and its functionality vary a lot. The bridge reminds us of the adapter pattern, but the difference is that the adapter pattern is used when something is already there and you cannot change it, while the bridge design pattern is used when things are being built. It helps us to avoid ending up with multiple concrete classes that will be exposed to the client. You will get a clearer understanding when we delve deeper in the topic, but for now, let's imagine that we want to have a FileReader class that supports multiple different platforms. The bridge will help us end up with FileReader, which will use a different implementation, depending on the platform. In Scala, we can use self-types in order to implement a bridge design pattern.

The composite design pattern

The composite is a partitioning design pattern that represents a group of objects that are to be treated as only one object. It allows developers to treat individual objects and compositions uniformly and to build complex hierarchies without complicating the source code. An example of composite could be a tree structure where a node can contain other nodes, and so on.

The facade design pattern

The purpose of the facade design pattern is to hide the complexity of a system and its implementation details by providing a simpler interface to use to the client. This also helps to make the code more readable and to reduce the dependencies of the outside code. It works as a wrapper around the system that is being simplified, and of course, it can be used in conjunction with some of the other design patterns we mentioned previously.

The flyweight design pattern

The flyweight design pattern provides an object that is used to minimize memory usage by sharing it throughout the application. This object should contain as much data as possible. A common example given is a word processor, where each character's graphical representation is shared with the other same characters. The local information then is only the position of the character, which is stored internally.

The proxy design pattern

The proxy design pattern allows developers to provide an interface to other objects by wrapping them. They can also provide additional functionality, for example, security or thread-safety. Proxies can be used together with the flyweight pattern, where the references to shared objects are wrapped inside proxy objects.

Behavioral design patterns

Behavioral design patterns increase communication flexibility between objects based on the specific ways they interact with each other. Here, creational patterns mostly describe a moment in time during creation, structural patterns describe a more or less static structure, and behavioral patterns describe a process or flow. They simplify this flow and make it more understandable. The main features of behavioral design patterns are as follows:

What is being described is a process or flow
The flows are simplified and made understandable
They accomplish tasks that would be difficult or impossible to achieve with objects

In this article, we will focus our attention on the following behavioral design patterns:

Value object
Null object
Strategy
Command
Chain of responsibility
Interpreter
Iterator
Mediator
Memento
Observer
State
Template method
Visitor

The following subsections will give brief definitions of the aforementioned behavioral design patterns.

The value object design pattern

Value objects are immutable and their equality is based not on their identity, but on their fields being equal. They can be used as data transfer objects, and they can represent dates, colors, money amounts, numbers, and so on. Their immutability makes them really useful in multithreaded programming. The Scala programming language promotes immutability, and value objects are something that naturally occur there.

The null object design pattern

Null objects represent the absence of a value and they define a neutral behavior. This approach removes the need to check for null references and makes the code much more concise. Scala adds the concepts of optional values, which can replace this pattern completely.

The strategy design pattern

The strategy design pattern allows algorithms to be selected at runtime. It defines a family of interchangeable encapsulated algorithms and exposes a common interface to the client. Which algorithm is chosen could depend on various factors that are determined while the application runs. In Scala, we can simply pass a function as a parameter to a method, and depending on the function, a different action will be performed.

The command design pattern

This design pattern represents an object that is used to store information about an action that needs to be triggered at a later time. The information includes the following:

The method name
The owner of the method
Parameter values

The client then decides which commands to be executed and when by the invoker. This design pattern can easily be implemented in Scala using the by-name parameters feature of the language.

The chain of responsibility design pattern

The chain of responsibility is a design pattern where the sender of a request is decoupled from its receiver. This way, it makes it possible for multiple objects to handle the request and to keep logic nicely separate. The receivers form a chain where they pass the request, and if possible, they process it, and if not, they pass it to the next receiver. There are variations where a handler might dispatch the request to multiple other handlers at the same time. This somehow reminds of function composition, which in Scala can be achieved using the stackable traits design pattern.

The interpreter design pattern

The interpreter design pattern is based on the possibility to characterize a well-known domain with a language with strict grammar. It defines classes for each grammar rule in order to interpret sentences in the given language. These classes are likely to represent hierarchies as grammar is usually hierarchical as well. Interpreters can be used in different parsers, for example, SQL or other languages.

The iterator design pattern

The iterator design pattern is when an iterator is used to traverse a container and access its elements. It helps to decouple containers from the algorithms performed on them. What an iterator should provide is sequential access to the elements of an aggregate object without exposing the internal representation of the iterated collection.

The mediator design pattern

This pattern encapsulates the communication between different classes in an application. Instead of interacting directly with each other, objects communicate through the mediator, which reduces the dependencies between them, lowers the coupling, and makes the overall application easier to read and maintain.

The memento design pattern

This pattern provides the ability to rollback an object to its previous state. It is implemented with three objects: originator, caretaker, and memento. The originator is the object with the internal state; the caretaker will modify the originator, and a memento is an object that contains the state that the originator returns. The originator knows how to handle a memento in order to restore its previous state.

The observer design pattern

This pattern allows the creation of publish/subscribe systems. There is a special object called subject that automatically notifies all the observers when there are any changes in the state. This design pattern is popular in various GUI toolkits and generally where event handling is needed. It is also related to reactive programming, which is enabled by libraries such as Akka.

The state design pattern

This pattern is similar to the strategy design pattern, and it uses a state object to encapsulate different behavior for the same object. It improves the code's readability and maintainability by avoiding the use of large conditional statements.

The template method design pattern

This pattern defines the skeleton of an algorithm in a method and then passes some of the actual steps to the subclasses. It allows developers to alter some of the steps of an algorithm without having to modify its structure. An example of this could be a method in an abstract class that calls other abstract methods, which will be defined in the children.

The visitor design pattern

The visitor design pattern represents an operation to be performed on the elements of an object structure. It allows developers to define a new operation without changing the original classes. Scala can minimize the verbosity of this pattern compared to the pure object-oriented way of implementing it by passing functions to methods.

Functional design patterns

We will be looking into all of the preceding design patterns from the point of view of Scala. This means that they will look different than in other languages, but they've still been designed not specifically for functional programming. Functional programming is much more expressive than object-oriented programming. It has its own design patterns that help making the life of a programmer easier. We will focus on:

Monoids
Monads
Functors

After we've looked at some Scala functional programming concepts, and we've been through these, we will mention some interesting design patterns from the Scala world.

A brief explanation of the preceding listed patterns will follow in the next few subsections.

Monoids

Monoid is a concept that comes from mathematics. For now, it will be enough to remember that a monoid is an algebraic structure with a single associative binary operation and an identity element. Here are the keywords you should remember:

The associative binary operation. This means (a+b)+c = a+(b+c)
The identity element. This means a+i = i+a = a. Here, the identity is i

What is important about monoids is that they give us the possibility to work with many different types of values in a common way. They allow us to convert pairwise operations to work with sequences; the associativity gives us the possibility for parallelization, and the identity element allows us to know what to do with empty lists. Monoids are great to easily describe and implement aggregations.

Monads

In functional programming, monads are structures that represent computations as sequences of steps. Monads are useful for building pipelines, adding operations with side effects cleanly to a language where everything is immutable, and implementing compositions. This definition might sound vague and unclear, but explaining monads in a few sentences seems to be something hard to achieve. We will try to show why monads are useful and what they can help with as long as developers understand them well.

Functors

Functors come from a category theory, and as for monads, it takes time to explain them properly. For now, you could remember that functors are things that can allow us to lift a function of the type A => B to a function of the type F[A] => F[B].

Scala-specific design patterns

The design patterns in this group could be assigned to some of the previous groups. However, they are specific to Scala and exploit some of the language features that we will focus on, and we've decided to place them in their own group.

We will focus our attention on the following ones:

The lens design pattern
The cake design pattern
Pimp my library
Stackable traits
The Type class design pattern
Lazy evaluation
Partial functions
Implicit injection
Duck typing
Memoization

The next subsections will give you some brief information about these patterns.

The lens design pattern

The Scala programming language promotes immutability. Having objects immutable makes it harder to make mistakes. However, sometimes mutability is required and the lens design pattern helps us achieve this nicely.

The cake design pattern

The cake design pattern is the Scala way to implement dependency injection. It is something that is used quite a lot in real-life applications, and there are numerous libraries that help developers achieve it. Scala has a way of doing this using language features, and this is what the cake design pattern is all about.

Pimp my library

Many times, engineers need to work with libraries, which are made to be as generic as possible. Sometimes, we need to do something more specific to our use case, though. The pimp my library design pattern provides a way to write extension methods for libraries, which we cannot modify. We can also use it for our own libraries as well. This design pattern also helps to achieve a better code readability.

Stackable traits

The stackable traits is the Scala way to implement the decorator design pattern. It can also be used to compose functions, and it's based on a few advanced Scala features.

The type class design pattern

This pattern allows us to write generic code by defining a behavior that must be supported by all members of a specific type class. For example, all numbers must support the addition and subtraction operations.

Lazy evaluation

Many times, engineers have to deal with operations that are slow and/or expensive. Sometimes, the result of these operations might not even be needed. Lazy evaluation is a technique that postpones the operation execution until it is actually needed. It could be used for application optimization.

Partial functions

Mathematics and functional programming are really close together. As a consequence, there are functions that exist that are only defined for a subset of all the possible input values they can get. A popular example is the square root function, which only works for non-negative numbers. In Scala, such functions can be used to efficiently perform multiple operations at the same time or to compose functions.

Implicit injection

Implicit injection is based on the implicit functionality of the Scala programming language. It automatically injects objects whenever they are needed, as long as they exist in a specific scope. It can be used for many things, including dependency injection.

Duck typing

This is a feature that is available in Scala and is similar to what some dynamic languages provide. It allows developers to write code, which requires the callers to have some specific methods (but not implement an interface). When someone uses a method with a duck type, it is actually checked during compile time whether the parameters are valid.

Memoization

This design pattern helps with optimization by remembering function results, based on the inputs. This means that as long as the function is stable and will return the same result when the same parameters are passed, one can remember its results and simply return them for every consecutive identical call.

How to choose a design pattern

As we already saw, there is a huge number of design patterns. In many cases, they are suitable to be used in combinations as well. Unfortunately, there is no definite answer about how to choose the concept of designing our code. There are many factors that could affect the final decision, and you should ask yourselves the following questions:

Is this piece of code going to be fairly static or will it change in the future?
Do we have to dynamically decide what algorithms to use?
Is our code going to be used by others?
Do we have an agreed interface?
What libraries are we planning to use if any?
Are there any special performance requirements or limitations?

This is by no means an exhaustive list of questions. There are a lot of amount of factors that could dictate our decision in how we build our systems. It is, however, really important to have a clear specification, and if something seems missing, it should always be checked first.

They should help you ask the right questions and take the right decision before going on and writing code.

Setting up the development environment

This will aim to give real code examples for you to run and experiment with. This means that it is important to be able to easily run any examples we have provided here and not to fight with the code. We will do our best to have the code tested and properly packaged, but you should also make sure that you have everything needed for the examples.

Installing Scala

Of course, you will need the Scala programming language. It evolves quickly, and the newest version could be found at http://www.scala-lang.org/download/. There are a few tips about how to install the language in your operating system at http://www.scala-lang.org/download/install.html.

Tips about installing Scala

You can always download multiple versions of Scala and experiment with them. I use Linux and my tips will be applicable to Mac OS users, too. Windows users can also do a similar setup. Here are the steps:

Install Scala under /opt/scala-{version}/. Then, create a symlink using the following command: sudo ln -s /opt/scala-{version} scala-current. Finally, add the path to the Scala bin folder to my .bashrc (or equivalent) file using the following lines: export SCALA_HOME=/opt/scala-current and export PATH=$PATH:$SCALA_HOME/bin. This allows us to quickly change versions of Scala by just redefining the symlink.

Another way to experiment with any Scala version is to install SBT (you can find more information on this). Then, simply run sbt in your console, type ++ 2.11.7 (or any version you want), and then issue the console command. Now you can test Scala features easily.

Using SBT or Maven or any other build tool will automatically download Scala for you. If you don't need to experiment with the console, you can skip the preceding steps.

Using the preceding tips, we can use the Scala interpreter by just typing scala in the terminal or follow the sbt installation process and experiment with different language features in the REPL.

Scala IDEs

There are multiple IDEs out there that support development in Scala. There is absolutely no preference about which one to use to work with the code. Some of the most popular ones are as follows:

IntelliJ
Eclipse
NetBeans

They contain plugins to work with Scala, and downloading and using them should be straightforward.

Summary

By now, we have a fair idea about what a design pattern means and how it can affect the way we write our code. We've iterated the most famous design patterns out there, and we have outlined the main differences between them. We saw that in many cases, we could use Scala's features in order to make a pattern obsolete, simpler, or different to implement compared to the classical case for pure object-oriented languages.

Knowing what to look for when picking a design pattern is important, and you should already know what specific details to watch out for and how important specifications are.