Functional Programming vs OOP

Functional Programming vs OOP

Functional programming and Object-Oriented Programming (OOP) are two different approaches to software development that have been widely used in the industry. Both paradigms have their own strengths and weaknesses, and the choice between them often depends on the specific needs of a project. This blog will mainly focus on the difference of Functional programming vs OOP.

Functional programming emphasizes the use of functions and immutability, while OOP focuses on the modeling of real-world objects and their interactions. In this article, we will explore the key differences between functional programming and OOP, and provide examples of when each approach is best suited. 

Whether you are a beginner or an experienced programmer, understanding the fundamental concepts of both paradigms will help you make informed decisions when choosing the right approach for your next project.

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What Is Functional Programming?

Functional Programming is a programming paradigm in which you build a program by applying and composing functions. You can use this programming model to create various applications, including games and animation. In addition, you can use it to write scripts and other applications with a high level of control and flexibility.

Immutable data

Immutable data is a vital part of Functional Programming. Not only does it reduce the chance of error and inconsistency, but it also helps speed up the process. However, immutability has its downsides, too. If a program is not designed properly, it can cause delays, side effects, and less-than-optimal performance.

A functional programming language generally has clear-cut methods for implementing immutability. Most of these methods do not apply when the code is laden with side effects.

A vital function of an immutable object is that it cannot be modified after creation. This is especially useful for multithreaded applications. Since immutable objects do not alter previous versions, they do not need to be synchronized.

Also read: JavaScript vs Typescript

First-class functions

First-class functions are a significant necessity for functional programming. This is because they provide a separation of concerns. They allow the function to be passed around as a value, like any other variable. The concept is also related to the mathematical concept of higher-order functions.

Higher-order functions take a first-class function as an argument and then return a new function. These functions can be used in the same way as ordinary values, but they have a more concrete meaning.

In some programming languages, these functions are called closures. Closures are similar to a function, except that they reference variables outside of the function’s lexical scope. A closure can be accessed even if the enclosing scope has been discarded.

Referential transparency

Referential transparency is a characteristic property of mathematical expressions. It means that the value of an expression does not depend on the values of its constituent expressions. That is, an expression can be rewritten in any language without losing its meaning.

Referential transparency is a powerful modularization technique. It lets you reduce code to a single piece that fits in your head. A referentially transparent function is also easy to optimize.

There are two primary types of referential transparency. An explicit and implicit one. In an explicit referential transparency, the value of a function is replaceable with the result. This can be an operator, an expression, or a function call.

Pure functions

Using pure functions in functional programming can be a big step towards improving your code. You’ll discover that they have numerous benefits. For one thing, they are deterministic and predictable.

In addition, pure functions have no side effects. While they can change state, they cannot alter other application parts. This means that they’re safe to use and more reusable.

As a result, they’re great for unit testing. You can automate test cases for asserting the return value of a function.

Pure functions are also great for debugging. Since they only depend on inputs and outputs, they can’t cause unexpected outcomes. If you have a bug in your code, it’s much easier to figure out why.

Avoiding constructions like If-Else statements or loops

Functional programming uses a variety of constructs to make the program easier to read and maintain. These include functions, sequence functions, and immutable data structures. Here is a look at how these can help avoid constructions like if-then-else statements or loops.

In functional programming, a function’s output depends only on its input. For example, if you pass a string into a function, that string will be returned. However, if you also pass a numeric argument to that function, that value will depend on the value you pass.

Functional programming also uses monads to isolate side effects. This makes it possible to isolate function calls and ensures that their timing and state are independent.

Object-Oriented Programming or OOP

Many people use the term “object-oriented programming” to describe the process of designing computer programs in a particular way. The process includes things such as encapsulation, inheritance, and polymorphism. However, it’s essential to realize that this programming approach is one of many available. You can also create software using a more traditional, sequential approach.


Polymorphism in object-oriented programming is the process of creating interchangeable objects and components. It is used to maximize reusability. This technique is useful in programming because it reduces coupling between functions.

One of the most useful features of polymorphism is allowing a function or method to operate on different data types. It can be implemented using methods overloading, function overloading, and operator overloading.

Another major feature of polymorphism is method overriding. This is achieved through the use of virtual functions. For instance, a Move function could display flying on the screen when the Fish class object is run. However, a subclass of the Fish class might implement the same Move method differently.

Polymorphism is an important part of Object Oriented Programming because it helps write creative code blocks. It also improves code maintenance.


Inheritance is an essential concept in object-oriented programming. It links various classes together and provides a clear code structure. It improves code reusability, reduces code replication, and helps increase interdependence among a software system’s components.

Inheritance is the process by which a class gains the properties and behavior of another class. There are two primary forms of inheritance: single and multiple.

Single inheritance is the simplest form. A subclass inherits only the public and protected methods of the parent class.

Multiple inheritances are a more complex form of inheritance. This allows classes to be combined without restriction. However, it is prone to misuse.

Single inheritance is the simplest form and is limited to one base class. For example, a class named “human” can inherit the weight and height of the “human” class.


Encapsulation is a core concept of object-oriented programming (OOP). The concept hides the internal workings of an object and its member variables from the user. This enables the object to be changed without disrupting other parts of the program.

Encapsulation is also used to prevent unauthorized access to data. It makes the code easier to understand and debug.

Object-oriented programming is all about solving problems. Developers model real-world entities, such as cars, using abstraction. Increasing the level of abstraction leaves out details and simplifies things. A car’s movements are described in abstract concepts such as “motion.”

By encapsulating objects, developers gain control over their behavior and how the object interacts with other objects. Encapsulation also allows for the validation of user inputs.


In object-oriented programming, the coupling is the degree of interdependence between software modules. Coupling is essential for a number of reasons. For one, it is a sign of good OO design. But coupling is not a magic bullet and is impossible to eliminate.

Coupling can be loose or tight. While tightly coupled modules may be hard to maintain, they have the benefit of reducing code complexity. However, they also can cause bugs to occur.

The loosest possible coupling is when modules have very little direct interaction. This can be achieved by using interfaces. Another example is inheritance. Using inheritance requires dynamic coupling, which means changing the base class of a module can be a bad idea.

A more complex type of coupling is semantic coupling. Semantic coupling deals with the similarities and differences between two or more program objects.

Functional Programming vs OOP


Functional programming is an effective approach to solving complex problems. Its benefits include lazy evaluation and modular code. These features make it easier for the development team to deal with different environments.

Object-oriented programming, on the other hand, is more complicated and can be challenging to debug. The essential elements of OOP are methods, objects, and inheritance. They are used to encapsulate the state. This type of programming is most effective for programs with a fixed number of operations and entities.


There are many reasons to prefer one programming style over the other. For example, the Object Oriented Programming (OOP) style offers a highly customizable environment and provides a platform for programmers to write code quickly and effectively. On the other hand, Functional Programming (FP) is more suited to writing less complicated code, making programming more accessible to newcomers.

Modularity vs. abstraction

Modularity vs. abstraction is two of the most important concepts when choosing a programming paradigm. Each has its pros and cons. The simplest way to compare them is to think of the data that make up a program. These are things like variables, calculations, and behaviors. Object-oriented and functional programming use different approaches to address these issues.

Functional programming emphasizes efficiency and reusability. It also uses the concept of encapsulation, whereby objects can contain other objects and share a common context. In the same way, OOP relies on combining data and behaviors.

In FP, the most fundamental component of a computer program is data. Using functions is a fundamental feature. Other elements include nested functions, variables, and methods.

Object-oriented programming uses a class-based approach to encapsulation. Classes can inherit properties and methods from other classes. They can also be defined as subtypes of other classes. This makes it easier to implement a system’s state.

Referential transparency vs. polymorphism

Referential transparency is a term that describes a programming language feature that guarantees the same result for each call to a function. Compared to a non-transparent system, referential transparency can make it easier to understand and test programs and simplify refactoring and unit testing.

In functional languages, functions are referentially transparent. This means that the value of the function is not affected by the name of the referent unless the referent is replaced. As such, the function cannot change the global state. However, it can modify the internal state and track changes with simple tricks.

Referential transparency allows a function to be called without requiring sequence points. A referentially transparent program can be evaluated at any time. Therefore, the behavior of the program does not depend on the input.

Referentially transparent code also makes it possible for programs to be written in any context. For instance, a referentially transparent function can be memoized, which helps to cache computed values. Similarly, the value of a non-local variable can be statically bound to a named value.

Object-oriented programming vs. FP

Object-oriented programming (OOP) and functional programming (FP) are not mutually exclusive. There are many practical benefits to both styles. However, some developers believe that FP is better for some projects, while OOP is better for others.

OOP is a programming style that allows you to program in a class, with the object as a simulated reality representing a real-world concept. This enables you to simplify and visualize the complex concepts you are working with.

FP is a programming style that focuses on program state management. The idea is to make the right assumptions about the changes in the program’s state. Unlike OO, FP uses functions over data to describe the world’s state. It has a compact code base and predictable variable types.

In some functional languages, pattern matching is part of idiomatic code. It is also helpful in returning functions from other functions.

Both OOP and FP allow for the creation of flexible and robust systems. They are easier to write and debug than imperative programming, which tries to keep everything in one place.

How They Compliment Each Other

In terms of programming, there are two main paradigms: functional programming (FP) and object-oriented programming (OOP). Both paradigms have advantages and disadvantages, so you should consider both before choosing one.

Functional programming is focused on efficiency and bug-free code. It also offers lazy evaluation, nested functions, and reusable functions. For example, Python supports functions as first-class citizens, meaning they can be assigned to variables. OOP could be more efficient. The program can run slowly, and it is harder to modify.

Object-oriented programming is a paradigm that puts objects on a pedestal. They can be created, inherited from others, and used as subtypes of other objects. This allows them to contain variables, methods, and other properties.

FP and OOP complement each other. They work together to alleviate some of the most common challenges. However, in order to achieve the benefits, you must have a good understanding of both languages.

OOP is more beneficial for small, simple projects, but FP is better for complex systems. FP code is compact and easy to debug.


  • As opposed to OOP, which is based on objects and models, FP is based on data and their transformations through functions.
  • FP follows the declarative programming paradigm and OOP follows the imperative programming paradigm.
  • FP utilizes immutable data while OOP utilizes mutable data.
  • Parallel programming is allowed both in FP and OOP but OOP allows parallel programming without high-level abstraction.
  • FP uses recursions for iterations while OOP uses cycles.
  • FP uses commands randomly whereas OOP uses them in set order. 


In conclusion, functional programming is more concise and efficient than OOP. This can be seen in the code, which is easier to read and understand. Functional programming also allows for cleaner interfaces, making it more likely that a library will be compatible with your code.