Introduction
This is not the first post blog I am writing about design patterns. In my recent posts, I’ve received positive feedback on this topic because apparently using design patterns is not a common practice in the Python world. I think people should learn these patterns to enhance and improve their code. Moreover, today AI software is heavily based on Python, so I think that these tutorials are useful to all the people dealing with AI. I will run my code on the Deepnote platform.
What is a design pattern?
Design patterns provide well-defined solutions to problems that recur very often when designing software. Rather than solve the same issue over and over again, these patterns offer reusable solutions, accelerating the whole development process.
Design patterns essentially provide a robust and tested blueprint to address specific problems optimally, making our lives easier.
There are various types of design patterns, generally categorized into three groups:
- Creational Patterns: These focus on the creation of objects, providing mechanisms for object creation while keeping the system flexible and efficient.
- Structural Patterns: They revolve around the composition of classes and objects, dealing with the relationships between different components to form larger structures.
- Behavioural Patterns: This category governs how classes and objects interact, outlining the distribution of responsibilities among them. It defines protocols for communication and collaboration within a software system.”
The Problem
When we work on big projects using Python, we generally adopt an object-oriented programming methodology to make the code more readable. Usually, we end up having a lot of classes and tons of objects.