An Overview of the Course
Explore the full range of topics covered in this course focusing on clean code principles and Python best practices. Understand fundamental coding guidelines, advanced Python features like decorators and generators, and essential software design principles to write maintainable and scalable code. Discover how unit testing and design patterns contribute to clean architecture and adaptable software systems.
We have reached the end of this course, so let's briefly go over all the concepts we have covered.
Basic coding guidelines
We discussed that adherence to coding styles or guidelines is important for multiple reasons. We agreed that this is a condition that is necessary, but not sufficient, and since it is a minimal requirement every solid project should comply with, it is clear that it is something we better leave to the tools. Therefore, automating all of these checks becomes critical, and in this regard, we have to keep in mind how to configure tools such as mypy, pylint, black, and others.
We then explored the core of Python: its protocols and magic methods. It should be clear by now that the best way of having Pythonic, idiomatic code is not only by following the formatting conventions, but also by taking full advantage of all the features Python has to offer. This means that we can write more maintainable code by using a particular magic method, a context manager, or writing more concise statements by using comprehensions and assignment expressions.
Software engineering principles
Moving forward, our focus shifted towards understanding several principles to achieve a clean design. Understanding that the code is part of the design is key to achieving high-quality software. By applying DbC, we can create components that are guaranteed ...