Object-oriented programming is an approach to computer programming that is increasingly used in the field of software development but also for Data Science. This article will find its definition, advantages, and how it works.
Also called “OOP,” object-oriented programming is a computer programming model. Rather than organizing software design around functions or logic, it manages it around data or “objects.” An object can be defined as a field of data with its attributes and unique behavior. As a result, rather than concentrating on the logic required to manipulate objects, OOP programming focuses on the objects themselves.
How does object-oriented programming work?
The first step in object-oriented programming is collecting all the objects the programmer wants to manipulate. It is also necessary to identify the links and connections between these objects. It is called “Data Modeling.” Once an object is known, it is labeled with an object “class” that defines the type of data it contains and any logical sequence for manipulating it.
Object-oriented programming can be done in a variety of programming languages. One of the oldest is Simula, and other popular languages include Python, Java, Javascript, C++, Visual Basic.NET, Ruby, Scala, and PHP. Whatever language is chosen by a programmer, it is necessary to know it well so the code is written without mistakes and no issues and bugs occur afterward. It can be a problem for a novice in programming because no beginner knows all the details about programming languages, as, for example, a professional does. The good news is that some very experienced programming specialists, such as, for instance, competent coders from Wow Assignment, are ready to provide the best practical help in programming.
The principles of object-oriented programming
Object-oriented programming is based on several fundamental principles. First, “encapsulation” refers to the fact that each object is categorized in a specific object “class.” Objects not of the same class do not have access to it and cannot make changes. They can only call a list of public functions or methods. It strengthens security and avoids data corruption.
The second principle is abstraction. Objects reveal only the internal mechanisms relevant to the use of other objects, hiding any unnecessary implementation code. It makes it easier for developers to make changes and additions over time.
On the other hand, the inheritance principle allows adding relationships and subclasses between objects. It will enable developers to reuse common logic while preserving a unique hierarchy. This feature allows a complete data analysis, reduces development time, and offers higher precision.
Finally, polymorphism is the last specificity of object-oriented programming. Objects can take different forms depending on the context. Furthermore, the program automatically determines which user is required for each execution of the same object, eliminating the need to duplicate code.
Object-Oriented Programming and Data Science
For software development as well as for Data Science, object-oriented programming is more and more used. In the past, data scientists typically wrote computer code in notebooks or as simple Python scripts. Object-oriented programming was not commonly used in data science, whether cleaning data, developing models, or executing them.
Similarly, data engineers could use object-oriented languages and cloud technologies to store, cleanse, and deliver data to teams but mainly were content with Lambda functions on AWS or open-source libraries.
Now, many data scientists have realized the benefits of object-oriented programming. This approach allows code to be production-ready, readable, and extensible to new use cases.
What are the advantages of object-oriented programming?
This approach is particularly suitable for large and complex programs that are updated regularly. It is also ideal for collaborative development, where projects are divided into groups.
Object-oriented programming has several advantages, especially reusability, elasticity, and efficiency. These principles can also be applied when using microservices. Nevertheless, this approach also has its drawbacks. One of the main criticisms of object-oriented programming is that it leaves out computation and algorithms, which are essential in software development.
Conclusion:
Object-oriented code is typically more complex and takes longer to compile. As a result, some developers opt for functional, structured, or imperative programming alternatives. However, the most advanced programming languages allow for a combination of these different models. It is up to every programmer to choose what is best for them.
