Preface

Python rocks!

From the earliest version in the late 1980s to the current 3.9 version, Python has evolved with the same philosophy: providing a multi-paradigm programming language with readability and productivity in mind.

Initially, people used to see Python as yet another scripting language. Many of them didn't believe it could be used to build large and complex systems. But over the years, and thanks to some pioneer companies, it became obvious that Python could be used to build almost any kind of a software.

Although writing Python code is easy, making it readable, reusable, and easy to maintain is challenging. You can achieve those qualities only through good software artistry and technique, which you will build gradually by constantly learning and gaining experience.

This book was written to express many years of professional experience in building all kinds of applications with Python, from small system scripts done in a couple of hours to very large applications written by dozens of developers over several years.

This book is divided into three parts:

1. Knowing your tools: Chapters 1 to 4 focus on basic elements of Python programmer's toolbelt. From productivity tools, through modern environments, to the newest syntax elements introduced in the latest Python releases. It also offers a safe landing zone for programmers who have experience with other programming languages and are just starting to learn more advanced Python.
2. Building applications with Python: Chapters 5 to 9 are all about design patterns, programming paradigms, and metaprogramming techniques. We will try to build some small but useful programs and will be often taking a deeper look into application architecture. We will also go a bit beyond Python and see how we can integrate code written using other programming languages.
3. Maintaining Python applications: Chapters 10 to 13 will be discussing all the things that usually happen after the application "goes live". We will showcase tools and techniques that help to keep applications easily maintainable and show how to approach common problems with packaging, deployment, monitoring, and performance optimization.

Who this book is for

The Python programming book is intended for expert programmers who want to learn about Python's advanced-level concepts and latest features.

This book is written for Python developers who wish to go further in mastering Python. And by developers, I mean mostly professional programmers who write Python software for a living. This is because it focuses mostly on tools and practices that are crucial for creating performant, reliable, and maintainable software in Python.

However, this does not mean that hobbyists won't find anything interesting. This book is great for anyone who is interested in learning advanced-level concepts with Python. Anyone who has basic Python skills should be able to follow the content of the book, although it might require some additional effort from less experienced programmers. It should also be a good introduction to the newest releases of Python for those who are still a bit behind and continue to use older versions of Python.

What this book covers

Chapter 1, Current Status of Python, showcases the current state of the Python language and its community. We will see how Python is constantly changing and why it is changing. We will learn what to do with old Python 2 code and how to be constantly up to date with what is currently happening in the Python community.

Chapter 2, Modern Python Development Environments, describes modern ways of setting up repeatable and consistent development environments for Python programmers. We will learn differences between application-level and system-level isolation. We will concentrate on two popular tools for environment isolation, virtualenv-type environments and Docker containers, but will also review other alternatives. At the end of the chapter, we will discuss common productivity tools that are extremely useful during development.

Chapter 3, New Things in Python, showcases recent Python language additions. We will review the most important Python syntax changes that happened in the last four releases of Python. We will also take a look at exciting changes that are scheduled for the next major Python release—Python 3.10.

Chapter 4, Python in Comparison with Other Languages, shows how Python compares to other languages. We will learn what programming idioms are and how to recognize them in code. We will take a deeper look into key elements of Python's object-oriented programming model and how it is different from other object-oriented programming languages but will also discuss other popular programming language features like descriptors, decorators, and dataclasses. This chapter should allow programmers with experience in other languages to safely land in the Python ecosystem.

Chapter 5, Interfaces, Patterns, and Modularity, discusses elements of Python that allow for implementing various reusable design patterns. If focuses on the concept of class interfaces and how they can be implemented in Python. It also discusses inversion of control and dependency injection—two extremely useful but not necessarily popular programming techniques.

Chapter 6, Concurrency, explains how to implement concurrency in Python using different approaches and libraries. It features three major concurrency models: multithreading, multiprocessing and asynchronous programming. In this chapter we will learn key differences between those models and how to use them effectively.

Chapter 7, Event-Driven Programming, describes what event-driven programming is and how it relates to asynchronous programming and different concurrency models. We will present various approaches to event-driven programming along with useful libraries.

Chapter 8, Elements of Metaprogramming, presents an overview of common approaches to metaprogramming available to Python programmers. We will learn about common metaprogramming techniques like decorators, as well as metaclasses and code generation patterns.

Chapter 9, Bridging Python with C and C++, explains how to integrate code written in different languages in your Python application. We will learn when extensions in C can be useful and how to create them.

Chapter 10, Testing and Quality Automation, is about providing automated testing and quality processes. We will learn about a popular testing framework—Pytest—and many useful testing techniques. We will also cover tools that can be used to assess code quality metrics and improve code style in fully automated way.

Chapter 11, Packaging and Distributing Python Code, describes the current state of Python packaging and best practices for creating packages that are to be distributed as open source code in the Python Package Index (PyPI). We will also cover the topics of packaging applications for web development and creating standalone Python executables for desktop applications.

Chapter 12, Observing Application Behavior and Performance, discusses the topic of application observability. We will learn about Python logging systems, how to monitor application metrics and perform distributed transaction tracing. We will also learn how to scale simple observability practices to large-scale distributed systems.

Chapter 13, Code Optimization, discusses the basic rules of optimization that every developer should be aware of. We will learn how to identify application performance bottlenecks and how to use common profiling tools. We will also learn common optimization techniques and strategies that can be easily applied in many situations once you know where the bottleneck is.

To get the most out of this book

This book is written for developers who work under any operating system for which Python 3 is available.

This is not a book for beginners, so I assume you have Python installed in your environment or know how to install it. Anyway, this book takes into account the fact that not everyone needs to be fully aware of the latest Python features or officially recommended tools. This is why Chapter 2, Modern Python Development Environments provides an overview of recommended techniques and tools (such as virtual environments and pip) for setting up development environments.

Download the example code files

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Expert-Python-Programming-Fourth-Edition. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://static.packt-cdn.com/downloads/9781801071109_ColorImages.pdf.

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, and user input. Here is an example: "Any attempt to run the code that has such issues will immediately cause the interpreter to fail, raising a SyntaxError exception."

A block of code is set as follows:

print("hello world")

Any command-line input or output is written as follows:

$ python3 script.py

Some code examples will be representing input of shells. You can recognize them by specific prompt characters:

• >>> for interactive Python shell
• $ for Bash shell (macOS and Linux)
• > for CMD or PowerShell (Windows)

Some code or command-line examples will require providing your own name or values in provided placeholders. Placeholders will be surrounded with <> characters as in following example:

$ python <my-module-name>

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