Python for Software Design pdf epub mobi txt 电子书 下载 2026

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出版者:Cambridge University Press

作者:Allen B. Downey

出品人:

页数:270

译者:

出版时间:2009

价格:$39.99

装帧:Paperback

isbn号码:9780521725965

丛书系列:

图书标签:

• python
• 计算机
• 编程
• 英文版
• programming
• computer_science
• 中山图
• Python
• Python
• 软件设计
• 编程
• 算法
• 数据结构
• 面向对象
• 设计模式
• 软件工程
• 可维护性
• 代码质量

Python in Action: Crafting Robust and Scalable Software Solutions In the rapidly evolving landscape of software development, efficiency, readability, and the ability to adapt to new challenges are paramount. Python has emerged as a leading force, not just for its straightforward syntax and extensive libraries, but for its inherent power in enabling developers to build sophisticated, maintainable, and high-performing applications. "Python in Action: Crafting Robust and Scalable Software Solutions" is a comprehensive guide designed for those who have a foundational understanding of programming concepts and are ready to delve deeper into the practical application of Python for real-world software design. This book moves beyond introductory syntax, focusing on the principles, patterns, and advanced techniques that underpin the creation of well-architected and resilient software systems. This volume is meticulously structured to guide you through the entire lifecycle of software development, from initial conceptualization and design to implementation, testing, and deployment. We will explore how to leverage Python's versatile features to construct applications that are not only functional but also elegantly designed, easy to understand, and readily extensible. The emphasis is placed on building a solid understanding of best practices that will serve you throughout your career, regardless of the specific domain or project. Our journey begins with a deep dive into object-oriented programming (OOP) in Python, transcending basic class definitions. We will dissect the core principles of encapsulation, inheritance, and polymorphism, illustrating how to effectively apply them to model complex real-world entities and relationships within your software. The book will equip you with the knowledge to design classes that are cohesive, loosely coupled, and promote code reuse. You will learn to identify appropriate use cases for different OOP paradigms, such as composition over inheritance, and understand the benefits of design patterns like Factory, Singleton, and Strategy, not just as abstract concepts, but as practical solutions to common design problems. Following this, we will navigate the intricate world of data structures and algorithms from a Pythonic perspective. While Python offers built-in data structures like lists, dictionaries, and sets, understanding their underlying mechanics and performance characteristics is crucial for building efficient software. We will analyze the time and space complexity of various operations and explore more advanced data structures, such as heaps, queues, and trees, and demonstrate how to implement and utilize them effectively. This section will also cover fundamental algorithms for searching, sorting, and graph traversal, providing you with the tools to optimize your code for performance-critical applications. The aim is to cultivate an algorithmic mindset, enabling you to choose the most appropriate data structures and algorithms for any given task, leading to significant improvements in application speed and resource utilization. A cornerstone of robust software design is effective error handling and exception management. "Python in Action" dedicates significant attention to developing strategies for anticipating, identifying, and gracefully handling errors. You will learn to craft custom exceptions, implement robust `try-except-else-finally` blocks, and understand the importance of defensive programming. We will explore techniques for logging errors effectively, enabling easier debugging and monitoring of your applications in production environments. The goal is to build software that is resilient to unexpected inputs and conditions, minimizing the likelihood of crashes and providing a superior user experience. Modularity and code organization are critical for managing complexity in larger projects. This book will guide you in structuring your Python projects into logical modules and packages, promoting a clear separation of concerns. We will delve into the nuances of importing, namespace management, and the creation of reusable libraries. The principles of Don't Repeat Yourself (DRY) and Keep It Simple, Stupid (KISS) will be woven throughout this discussion, illustrating how well-organized code leads to improved maintainability, testability, and collaboration. You will learn to identify code duplication and refactor it effectively, leading to cleaner and more manageable codebases. Testing and debugging are indispensable components of the software development lifecycle. This volume will provide an in-depth exploration of Python's testing frameworks, primarily focusing on `unittest` and `pytest`. You will learn to write effective unit tests, integration tests, and functional tests, ensuring the correctness and reliability of your code at various levels. The importance of test-driven development (TDD) will be discussed, highlighting its benefits in driving design and ensuring comprehensive test coverage. Furthermore, we will cover advanced debugging techniques using Python's built-in debugger (`pdb`) and other popular tools, enabling you to efficiently pinpoint and resolve issues within your applications. Concurrency and parallelism are essential for building responsive and high-throughput applications. We will explore Python's capabilities in this domain, examining threading, multiprocessing, and asynchronous programming using `asyncio`. You will learn to distinguish between these approaches, understand their use cases, and implement them effectively to harness the power of multi-core processors and handle I/O-bound operations efficiently. This section will demystify concepts like race conditions, deadlocks, and the Global Interpreter Lock (GIL), providing practical strategies for writing correct and performant concurrent code. Throughout the book, we will emphasize the importance of clean code principles and idiomatic Python. This involves writing code that is not only functional but also readable, understandable, and adheres to community conventions. We will discuss techniques for improving code clarity, such as meaningful variable naming, writing concise functions, and employing docstrings effectively. Understanding Python's Style Guide (PEP 8) will be a foundational element, ensuring your code is consistent and easy for other developers to comprehend. Beyond core language features, "Python in Action" will touch upon essential tools and practices that are integral to professional software development. This includes an introduction to version control systems like Git, a fundamental tool for collaborative development and code management. We will also explore best practices for code packaging and distribution, enabling you to share your creations with others. Ultimately, "Python in Action: Crafting Robust and Scalable Software Solutions" is more than just a technical manual; it is a guide to cultivating a robust engineering mindset. It aims to empower you to think critically about software design, to make informed decisions about architecture and implementation, and to build Python applications that are not only functional today but are also built to last and adapt to the challenges of tomorrow. Whether you are looking to enhance your skills for personal projects, advance your career in software engineering, or contribute to open-source initiatives, this book will provide you with the knowledge and confidence to design and build exceptional software solutions using Python.

评分☆☆☆☆☆

This is a book for the beginners/student who want to use Python to finish their homework. But the author did not try to discuss why some data structure are immutable, other are mutable. It is based the data structure are designed for storing "by value" or ...

评分☆☆☆☆☆

This is a book for the beginners/student who want to use Python to finish their homework. But the author did not try to discuss why some data structure are immutable, other are mutable. It is based the data structure are designed for storing "by value" or ...

评分☆☆☆☆☆

This is a book for the beginners/student who want to use Python to finish their homework. But the author did not try to discuss why some data structure are immutable, other are mutable. It is based the data structure are designed for storing "by value" or ...

评分☆☆☆☆☆

This is a book for the beginners/student who want to use Python to finish their homework. But the author did not try to discuss why some data structure are immutable, other are mutable. It is based the data structure are designed for storing "by value" or ...

评分☆☆☆☆☆

This is a book for the beginners/student who want to use Python to finish their homework. But the author did not try to discuss why some data structure are immutable, other are mutable. It is based the data structure are designed for storing "by value" or ...

评分☆☆☆☆☆

老实讲，我买这本书的时候，是冲着它名字里“Software Design”这个部分去的，期望能学到一些能直接套用到我日常Java或C++项目中的设计原则，比如SOLID原则的Python式实现。然而，阅读体验却完全出乎意料，这本书的视角是自下而上、从Python的内核出发来重新诠释设计。它没有刻板地教你如何将面向对象的那套僵硬的结构硬塞给Python，反而是深入挖掘了Python独特的元编程能力、强大的内置数据结构如何巧妙地替代传统设计模式中的一些样板代码。举个例子，书中对“依赖注入”的讨论，没有直接引用依赖注入容器的概念，而是通过一个非常巧妙的例子，展示了如何使用函数式编程中的柯里化（Currying）和闭包，以一种更“Pythonic”的方式来达到松耦合的目的。这迫使我必须放下过去基于静态语言的思维定势，去拥抱Python作为一门动态、多范式的语言所提供的设计可能性。对于那些只满足于写脚本、做数据分析的读者来说，这本书的门槛可能会有点高，因为它要求你对“设计”二者的理解，已经达到了一定的成熟度，然后才能更好地吸收它提出的那些更贴近Python生态的创新思路。

评分☆☆☆☆☆

这本《Python for Software Design》的译本，我入手已经快半年了，说实话，它给我的震撼是相当大的。我原本以为这会是一本偏向于Python基础语法的工具书，毕竟书名里带着“Python”这个关键词，但翻开目录才发现，作者的野心远不止于此。它更像是一本披着Python外衣的，关于软件工程思想和设计模式的深度探讨。书中大量篇幅没有花在介绍`for`循环或者列表推导式上，而是聚焦于如何用Python的特性去实现那些在经典面向对象设计书籍里才出现的高级概念，比如策略模式、工厂模式在Python动态环境下的灵活变体，以及如何利用装饰器和元类来构建DSL（领域特定语言）。尤其让我印象深刻的是，作者在讲解抽象基类（ABC）和接口设计时，并非简单地罗列`abc`模块的使用，而是结合了大型项目中的实际案例，分析了在高度依赖鸭子类型（Duck Typing）的Python世界里，何时需要引入严格的契约约束，何时又该拥抱其灵活性。这种深入剖析语言哲学与工程实践之间微妙平衡的写作手法，让我对Python的理解提升到了一个新的维度，它不再仅仅是快速原型开发的利器，更是一种可以构建健壮、可维护、面向未来的复杂系统的强大工具。

评分☆☆☆☆☆

这本书的排版和章节组织简直是场灾难，我几乎是用生命在阅读。章节之间的逻辑跳跃性极大，上一章还在谈论如何使用生成器实现惰性加载的数据流管道，下一章就直接切入了异步编程模型的实现细节，中间几乎没有平滑的过渡。我感觉作者像是一个才华横溢但极度缺乏耐心去组织自己思路的教授，他把所有最深刻的见解都塞进了书里，但散落得像星尘一样。很多关键概念的解释，比如书中反复提到的“行为耦合度分析”，第一次出现时介绍得极其简略，我不得不翻阅后面几章，对比不同设计案例中的体现，才能勉强拼凑出一个完整的概念图景。我经常需要对照着我在GitHub上找到的一些开源项目的源码来阅读，才能真正理解作者在描述一个设计模式的“Python变种”时，他到底在代码层面暗示了什么。尽管阅读过程充满了挫败感，但一旦那些隐藏的联系被我自行打通的那一刻，那种豁然开朗的成就感，却是其他任何一本中规中矩的技术书籍都无法比拟的。它不是一本让你轻松吸收知识的书，而是一块需要你自己去雕琢的璞玉。

评分☆☆☆☆☆

这本书的语言风格呈现出一种非常鲜明的学术辩论色彩，它不像市面上流行的技术书籍那样，倾向于提供“最佳实践”或“权威答案”。相反，作者更热衷于提出问题，并列举多种设计路径的优缺点，仿佛在引导读者参与一场关于软件架构的研讨会。在讲解Python中的“魔术方法”（Magic Methods）时，作者并没有简单地将其视为语法糖，而是深入挖掘了它们在协议（Protocols）实现、运算符重载背后的语义学意义，并探讨了过度使用这些方法的潜在危险——即如何破坏代码的直观性和可预测性。这种处处充满反思和审慎态度的写作，迫使我不断地去质疑自己过去习以为常的编码习惯。比如，书中对于“面向对象与面向函数编程在Python中的融合点”的分析，充满了对两种范式边界模糊性的洞察，它没有简单地宣传哪种更好，而是展示了如何根据系统不同模块的特性，灵活地选择最合适的工具箱。这本书的价值，不在于它给你提供了可以直接复制粘贴的代码段，而在于它重塑了你对“好代码”和“健壮设计”的认知框架，这一点，是极其珍贵的。

评分☆☆☆☆☆

我必须承认，我在这本书里学到了很多关于Python语言底层机制如何支撑高级软件架构的知识，但同时，我也对它在“实践性”上的缺失感到非常遗憾。书中所有的代码示例，虽然在概念上是无可挑剔的完美体现，但它们往往被高度抽象化和简化了，缺乏真实世界业务场景的复杂性和粘稠感。例如，在讨论错误处理和异常链构建时，作者提供了一个极其优雅的装饰器解决方案，但这套方案在实际应用中，如何与现有的日志系统、分布式追踪机制，以及不同微服务间的通信协议错误码进行整合，书中完全没有涉及。这使得我阅读完后，获得的是一套精美的“蓝图”，却缺乏将这蓝图落地到水泥钢筋混凝土中的具体施工指南。这本书更像是一本哲学导论，而非一本实操手册。它教会了我“应该”如何设计软件，但当我合上书本，面对一个需要上线运营的真实项目时，我发现自己仍然需要花费大量时间去研究如何将书中的理想化设计，嫁接到那些充满历史包袱和性能瓶颈的现有代码库上。

评分☆☆☆☆☆

适合初学者的书，里面讲TkGUI比较多，比较吸引初学者。缺点是没好好讲网络和 字符串处理。。。总之比其它的python书还是有很多优点 另外附标题起得太奇怪

评分☆☆☆☆☆

给编程初学者的好书。

评分☆☆☆☆☆

真的能让我入门吗？

评分☆☆☆☆☆

真的能让我入门吗？

评分☆☆☆☆☆

适合初学者的书，里面讲TkGUI比较多，比较吸引初学者。缺点是没好好讲网络和 字符串处理。。。总之比其它的python书还是有很多优点 另外附标题起得太奇怪