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Mastering Python Design Patterns

Mastering Python Design Patterns

By : Kamon Ayeva, Kasampalis, Sakis Kasampalis
4.3 (8)
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Mastering Python Design Patterns

Mastering Python Design Patterns

4.3 (8)
By: Kamon Ayeva, Kasampalis, Sakis Kasampalis

Overview of this book

As software systems become increasingly complex, maintaining code quality, scalability, and efficiency can be a daunting challenge. Mastering Python Design Patterns is an essential resource that equips you with the tools you need to overcome these hurdles and create robust, scalable applications. The book delves into design principles and patterns in Python, covering both classic and modern patterns, and apply them to solve daily challenges as a Python developer or architect. Co-authored by two Python experts with a combined experience of three decades, this new edition covers creational, structural, behavioral, and architectural patterns, including concurrency, asynchronous, and performance patterns. You'll find out how these patterns are relevant to various domains, such as event handling, concurrency, distributed systems, and testing. Whether you're working on user interfaces (UIs), web apps, APIs, data pipelines, or AI models, this book equips you with the knowledge to build robust and maintainable software. The book also presents Python anti-patterns, helping you avoid common pitfalls and ensuring your code remains clean and efficient. By the end of this book, you'll be able to confidently apply classic and modern Python design patterns to build robust, scalable applications.
Table of Contents (17 chapters)
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Free Chapter
1
Part 1: Start with Principles
4
Part 2: From the Gang of Four
8
Part 3: Beyond the Gang of Four

To get the most out of this book

Use a machine with a recent version of Windows, Linux, or macOS.

Install Python 3.12. It is also useful to create a virtual environment from your Python installation so that when you add third-party modules required for following some of the chapters, you do not end up polluting your global Python. This is a fundamental best practice for productivity with Python, and you will find many resources on the Internet that explain how to do this.

Install and use Docker on your machine. This will help with the requirement of some external software services or tools, such as LocalStack (used in Chapter 6) and the Redis server (used in Chapter 8).

Software/hardware covered in the book

Operating system requirements

Python 3.12

Windows, macOS, or Linux

MyPy 1.10.0

Docker

Redis-server 6.2.6

LocalStack 3.4.0

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

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