Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Clean Code in Python

You're reading from   Clean Code in Python Develop maintainable and efficient code

Arrow left icon
Product type Paperback
Published in Jan 2021
Publisher Packt
ISBN-13 9781800560215
Length 422 pages
Edition 2nd Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Mariano Anaya Mariano Anaya
Author Profile Icon Mariano Anaya
Mariano Anaya
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

Preface 1. Introduction, Code Formatting, and Tools 2. Pythonic Code FREE CHAPTER 3. General Traits of Good Code 4. The SOLID Principles 5. Using Decorators to Improve Our Code 6. Getting More Out of Our Objects with Descriptors 7. Generators, Iterators, and Asynchronous Programming 8. Unit Testing and Refactoring 9. Common Design Patterns 10. Clean Architecture 11. Other Books You May Enjoy
12. Index

Who this book is for?

This book is suitable for all software engineering practitioners who are interested in software design or learning more about Python. It is assumed that the reader is already familiar with the principles of object-oriented software design and has experience writing code.

It will appeal to team leads, software architects and senior software engineers who want to learn good Python coding techniques to create projects from scratch or work on their legacy systems to save costs and improve efficiency.

The book is organized in such a way that the content is in increasing order of complexity. The first chapters cover the basics of Python, which is a good way to learn the main idioms, functions, and utilities available in the language. The idea is not just to solve some problems with Python, but to do so in an idiomatic way.

Experienced programmers will also benefit from the topics in this book, as some sections cover advanced topics in Python, such as decorators, descriptors, and an introduction to asynchronous programming. It will help the reader discover more about Python because some of the cases are analyzed from the internals of the language itself.

Scientists using Python for data processing can also benefit from the content of this book, and to that end, several parts of the book are dedicated to setting up projects from the ground up, in terms of tools, configuration of environments, and good practices to release software.

It is worth emphasizing the word "practitioners" in the first sentence of this section. This is a book that takes a pragmatic approach. Examples are limited to what the case study requires but are also intended to resemble the context of a real software project. It is not an academic book, and as such the definitions made, the remarks made, and the recommendations are to be taken with caution. The reader is expected to examine these recommendations critically and pragmatically rather than dogmatically. After all, practicality beats purity.

lock icon The rest of the chapter is locked
Next Section arrow right
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image