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Clean Code in Python
Clean Code in Python

Clean Code in Python: Refactor your legacy code base

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Clean Code in Python

Pythonic Code

In this chapter, we will explore the way ideas are expressed in Python, with its own particularities. If you are familiar with the standard ways of accomplishing some tasks in programming (such as getting the last element of a list, iterating, searching, and so on), or if you come from more traditional programming languages (like C, C++, and Java), then you will find that, in general, Python provides its own mechanism for most common tasks.

In programming, an idiom is a particular way of writing code in order to perform a specific task. It is something common that repeats and follows the same structure every time. Some could even argue and call them a pattern, but be careful because they are not designed patterns (which we will explore later on). The main difference is that design patterns are high-level ideas, independent from the language (sort of), but they do...

Indexes and slices

In Python, as in other languages, some data structures or types support accessing its elements by index. Another thing it has in common with most programming languages is that the first element is placed in the index number zero. However, unlike those languages, when we want to access the elements in a different order than usual, Python provides extra features.

For example, how would you access the last element of an array in C? This is something I did the first time I tried Python. Thinking the same way as in C, I would get the element in the position of the length of the array minus one. This could work, but we could also use a negative index number, which will start counting from the last, as shown in the following commands:

>>> my_numbers = (4, 5, 3, 9)
>>> my_numbers[-1]
9
>>> my_numbers[-3]
5

In addition to getting just one element...

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Key benefits

  • Save maintenance costs by learning to fix your legacy codebase
  • Learn the principles and techniques of refactoring
  • Apply microservices to your legacy systems by implementing practical techniques

Description

Python is currently used in many different areas such as software construction, systems administration, and data processing. 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. 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. By the end of the book, you will be proficient in applying industry approved coding practices to design clean, sustainable and readable Python code.

Who is this book for?

This book will appeal to team leads, software architects and senior software engineers who would like to work on their legacy systems to save cost and improve efficiency. A strong understanding of Programming is assumed.

What you will learn

  • Set up tools to effectively work in a development environment
  • Explore how the magic methods of Python can help us write better code
  • Examine the traits of Python to create advanced object-oriented design
  • Understand removal of duplicated code using decorators and descriptors
  • Effectively refactor code with the help of unit tests
  • Learn to implement the SOLID principles in Python

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Aug 29, 2018
Length: 332 pages
Edition : 1st
Language : English
ISBN-13 : 9781788835831
Category :
Languages :

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Product Details

Publication date : Aug 29, 2018
Length: 332 pages
Edition : 1st
Language : English
ISBN-13 : 9781788835831
Category :
Languages :

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Frequently bought together


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Total €76.96 €86.97 €10.01 saved
Modern Python Standard Library Cookbook
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Total €76.96€86.97 €10.01 saved Stars icon

Table of Contents

11 Chapters
Introduction, Code Formatting, and Tools Chevron down icon Chevron up icon
Pythonic Code Chevron down icon Chevron up icon
General Traits of Good Code Chevron down icon Chevron up icon
The SOLID Principles Chevron down icon Chevron up icon
Using Decorators to Improve Our Code Chevron down icon Chevron up icon
Getting More Out of Our Objects with Descriptors Chevron down icon Chevron up icon
Using Generators Chevron down icon Chevron up icon
Unit Testing and Refactoring Chevron down icon Chevron up icon
Common Design Patterns Chevron down icon Chevron up icon
Clean Architecture Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.7
(3 Ratings)
5 star 33.3%
4 star 33.3%
3 star 0%
2 star 33.3%
1 star 0%
Ivan and Zorro Jan 12, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
With so many Python books out there it’s hard to know which are worthwhile, particularly if you want to move beyond basics. This book is highly recommended for this category of Python programmer. It’s a must read for people working in agile development teams. It is well organized and written, containing material not treated elsewhere, or at least not in a single volume. Writing clean code goes beyond “having good documentation”. At a certain point this good documentation becomes more of a distraction than anything, particularly in Python. Well written Python should be the documentation minimalist’s dream and that is the main idea throughout this book: how to write efficient, properly documented Python code that is easily maintainable, by ourselves and other developers. The authors are not simply talking about code linting or analyzers, it’s more like the Zen of Python. They include examples of moving from some code to better code. The focus is on the readability of code since so many developers spend their time reading scads of code to add a simple feature, but there are also many examples of interesting ways to get things done in Python.
Amazon Verified review Amazon
Camila Corradi Nov 01, 2020
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
This book is great to improve OOP skills in Python. It gives you a view about what can be done in Python and good practices to follow when programming in Python. Also, the way the author involve while you are reading the book is very good and the pieces fit together nicely. My concern about the book is the lack of examples, don't get me wrong, the book has a good level of code, but I think that examples should be more didactic. Some of them, I needed to read and re-read several times to understand and get the idea.Anyway, is a great book and I really recommend it.
Amazon Verified review Amazon
Aris Oct 03, 2023
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
Very bad written. Some parts can be better explained
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