Learning when not to use OOP in Python
Python has the flexibility to develop programs using either OOP languages such as Java or using declarative programming such as C. OOP is always appealing to developers because it provides powerful tools such as encapsulation, abstraction, inheritance, and polymorphism, but these tools may not fit every scenario and use case. These tools are more beneficial when used to build a large and complex application, especially one that involves user interfaces (UIs) and user interactions.
If your program is more like a script that has to execute certain tasks and there is no need to keep the state of objects, using OOP is overkill. Data science applications and intensive data processing are examples where it is less important to use OOP but more important to define how to execute tasks in a certain order to achieve goals. A real-world example is writing client programs for executing data-intensive jobs on a cluster of nodes, such as Apache Spark for...
