Object-oriented programming is a computer programming approach that is increasingly used in software development, but also in Data Science. Find out everything you need to know: definition, benefits, how it works…
For software development as well as for Data Science, object-oriented programming is increasingly used. But in fact, what is it all about?
Also known as “OOP (object-oriented programming)object programming is a model of computer programming. Rather than organizing software design around functions or logic, it consists of organizing software design around data or “objects”.
A object can be defined as a data fieldwith its unique attributes and behaviour. Thus, rather than focusing 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 to collect all items that the programmer wishes to manipulate. It is also necessary to identify the links and connections between these objects. This is called “Data Modeling”.
As soon as an object is known, it is labeled with an object “class”. defining the type of data it contains and any logical sequence for manipulating it. Each logical sequence is a “method”. In addition, objects can communicate through interfaces called “messages”.
The principles of object-oriented programming
Object-oriented programming is based on several key principles. First of all, “Encapsulation.” means categorizing each object in a specific object “class”. Objects that are not of the same class do not have access to it, and cannot make changes. They can only use a list of public functions, or methods. This enhances security and prevents data corruption.
The second principle is that of abstraction. Objects only reveal internal mechanisms relevant to the use of other objects, hiding any unnecessary implementation code. This helps developers make changes and additions more easily over time.
The Principle ancestralallows you to add relationships and subclasses between objects. Thus, developers can reuse a common logic while preserving a single hierarchy. This feature allows for more complete data analysis, reduces development time, and offers a higher degree of accuracy.
I mean, come on, polymorphism is the last specificity of object-oriented programming. Objects can take different forms depending on the context. The program automatically determines what usage is required for each execution of the same object, eliminating the need to duplicate code.
Object Oriented Programming and Data Science
In the past, Data Scientists used to write computer code in notebooks or as simple Python scripts. Whether it was to cleanse data, develop models or run them, object-oriented programming was not commonly used in data science.
Similarly, the Data Engineers could use object-oriented languages and Cloud technologies to store, cleanse and transmit data to the teams, but were mainly satisfied with Lambda functions on AWS or open source libraries.
From now on, many Data Scientists have become aware the advantages of object-oriented programming. This approach allows the code to be production-ready, easily readable and extensible to new use cases.
What are the advantages of object-oriented programming?
This approach is particularly suitable for large and complex programmes that are updated very regularly. It is also appropriate for collaborative developmentThe projects are divided into groups.
Object-oriented programming has a number of advantages, including of reusability, elasticity and efficiency. These principles can also be applied when using microservices.
Nevertheless, this approach also has drawbacks. One of the main criticisms of object-oriented programming is that it leaves aside calculation and algorithms, which are essential in the field of software development.
Besides.., object-oriented code can be more complicated and take longer to compile. Some developers prefer to opt for alternatives such as functional programming, structured programming or imperative programming. However, the most advanced programming languages allow these different models to be combined.