Clean Code In Python : Download Free Book 
In all of these areas, experienced professionals can find examples of inefficiency, problems, and other perils, as a result of bad code. After reading this book, readers will understand these problems, and more importantly, how to correct them.
Clean Code In Python : Download Free Book
The book begins by describing the basic elements of writing clean code and how it plays an important role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. You will learn to implement the SOLID principles in Python and use decorators to improve your code. The book delves more deeply into object oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve software problems by implementing design patterns in your code. In the final chapter we break down a monolithic application to a microservice one, starting from the code as the basis for a solid platform.
In this chapter, we will explore the first concepts related to clean code, starting with what it is and what it means. The main point of the chapter is to understand that clean code is not just a nice thing to have or a luxury in software projects. It's a necessity. Without quality code, the project will face the perils of failing due to an accumulated technical debt.
After reading this chapter, you will have an idea of what clean code is, why it is important, why formatting and documenting the code are crucial tasks, and how to automate this process. From this, you should acquire the mindset for quickly organizing the structure of a new project, aiming for good code quality.
There is no sole or strict definition of clean code. Moreover, there is probably no way of formally measuring clean code, so you cannot run a tool on a repository that could tell you how good, bad, or maintainable or not that code is. Sure, you can run tools such as checkers, linters, static analyzers, and so on. And those tools are of much help. They are necessary, but not sufficient. Clean code is not something a machine or script could tell (so far), but rather something that us, as professionals, can decide.
Here is where the true nature of clean code lies. It depends on other engineers to be able to read and maintain the code. Therefore, we, as professionals, are the only ones who can judge this. Think about it; as developers, we spend much more time reading code than actually writing it. Every time we want to make a change or add a new feature, we first have to read all the surroundings of the code we have to modify or extend. The language (Python), is what we use to communicate among ourselves.
So, instead of giving you a definition (or my definition) of clean code, I invite you to go through the book, read all about idiomatic Python, see the difference between good and bad code, identify traits of good code and good architecture, and then come up with your own definition. After reading this book, you will be able to judge and analyze code for yourself, and you will have a more clear understanding of clean code. You will know what it is and what it means, regardless of any definition given to you.
There are a huge number of reasons why clean code is important. Most of them revolve around the ideas of maintainability, reducing technical debt, working effectively with agile development, and managing a successful project.
To sum this up, we can say that clean code has nothing to do with things like PEP-8 or coding styles. It goes way beyond that, and it means something more meaningful to the maintainability of the code and the quality of the software. However, as we will see, formatting the code correctly is important in order to work efficiently.
More importantly, we understood that clean code is something much more important than the structure and layout of the code. We have to focus on how the ideas are represented on the code to see if they are correct. Clean code is about readability, maintainability of the code, keeping technical debt to the minimum, and effectively communicating our ideas into the code so that others can understand the same thing we intended to write in the first place.
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When I started learning Python, my entire focus was on learning data science instead of the software engineering side of the programming language. I missed a lot of core concepts of the language that could have helped me write clean and reproducible code.
These bad coding practices cause delays and conflicts as it is hard to understand and optimize existing code. So, I started learning Python for software engineers. I took multiple courses and read books on mastering Python. These resources have helped me understand object-oriented programing, coding style, clean and reproducible code, refactoring, and test-driven development. This was not it. I wanted to learn more. I wanted to learn how to write elegant, compelling, and expressive code. This is where I found a free book called Pydon'ts, which helped me understand what I was missing in my coding practice.
Pydon'ts is totally free and has 330+ pages of pure knowledge. This book is for all professionals and enthusiasts who want to get better at writing elegant and production-ready code. Especially data scientists who are still writing code that is only understood by them. The book consists of 20 chapters that will teach you about Python built-ins and their various usage patterns. Each chapter contains an introduction, various usage patterns of a single function, coding examples, conclusions, and references. In short, every chapter is like a short blog explaining each concept in detail with a real project example.
The author of the book Rodrigo has been writing Python for seven and half years, and he has a blog Mathspp Blog, that covers interesting concepts of mathematics and programming language. He is highly respected in the Python community, and his vision is to teach people free of cost about the best practices of the Python language. Python is a rich language, and every chapter in this book explores a single feature in detail, accompanied by code examples covering all the angles.