精通Python编程第二版：深度探索高级概念

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"Expert Python Programming, 2nd Edition" 是一本深入探讨Python编程的书籍，适合已经有一定基础的读者进一步提升技能。本书基于Python 3.5版本，由Michał Jaworski和Tarek Ziadé合著，旨在帮助读者掌握最佳编码实践和高级编程概念。在Python编程的世界中，熟练掌握高级概念和最佳实践是成为顶尖程序员的关键。"Expert Python Programming, 2nd Edition" 提供了以下关键知识点： 1. **Python 3.5特性**：本书深入讲解Python 3.5中的新特性和改进，如新语法、性能优化以及库的更新，让读者能够充分利用这一版本的优势。 2. **编程最佳实践**：书中涵盖了代码风格、可读性、错误处理、单元测试、持续集成等编程规范，帮助读者编写出高质量的Python代码。 3. **高级数据结构和算法**：详细阐述了Python中的元组、列表、字典等复杂数据结构的高效使用，以及如何应用排序、搜索和图算法等，提升代码效率。 4. **函数式编程**：介绍Python中的函数式编程思想，如高阶函数、闭包、装饰器和生成器，让读者了解如何利用这些工具来简化代码并提高可维护性。 5. **面向对象编程**：详细解释类和对象的概念，以及继承、多态和封装等原则，帮助读者掌握面向对象设计技巧。 6. **并发与异步编程**：探讨Python中的线程、进程和协程，以及如何利用asyncio库进行异步操作，提升程序的并发性能。 7. **网络编程和Web开发**：介绍网络协议和套接字编程，以及如何使用Python构建Web应用，如Flask和Django框架的使用。 8. **科学计算和数据分析**：讨论NumPy、Pandas和Matplotlib等库在科学计算和数据分析中的应用，使读者能够处理大量数据并进行可视化。 9. **扩展Python**：包括C语言扩展Python模块的技巧，以及使用Cython和PyPy等工具提升Python代码执行速度的方法。 10. **调试和性能优化**：提供有效的调试策略和性能分析技巧，帮助读者识别并修复代码问题，优化程序性能。 11. **部署和自动化**：讲解如何配置服务器、自动化运维和持续集成，确保代码能在生产环境中稳定运行。这本书不仅适合有经验的Python开发者，也适合想要提升到更高层次的Python爱好者。通过阅读和实践书中的内容，读者可以提升自己的Python编程技能，成为一名真正的Python专家。

Table of Contents

[ ix ]

Using architectural trade-offs 405

Using heuristics and approximation algorithms 405

Using task queues and delayed processing 406

Using probabilistic data structures 410

Caching 411

Deterministic caching 412

Nondeterministic caching 415

Cache services 416

Memcached 416

Summary 419

Chapter 13: Concurrency 421

Why concurrency? 422

Multithreading 423

What is multithreading? 424

How Python deals with threads 425

When should threading be used? 426

Building responsive interfaces 426

Delegating work 426

Multiuser applications 427

An example of a threaded application 428

Multiprocessing 442

The built-in multiprocessing module 445

Using process pools 449

Using multiprocessing.dummy as a multithreading interface 450

Asynchronous programming 451

Cooperative multitasking and asynchronous I/O 452

Python async and await keywords 453

asyncio in older versions of Python 457

A practical example of asynchronous programming 458

Integrating nonasynchronous code with async using futures 461

Executors and futures 462

Using executors in an event loop 464

Summary 465

Chapter 14: Useful Design Patterns 467

Creational patterns 467

Singleton 468

Structural patterns 471

Adapter 472

Interfaces 474

Proxy 487

Facade 489

Preface

[ xii ]

What this book covers

Chapter 1, Current Status of Python, showcases the current state of the Python

language and its community. It shows how Python is constantly changing, why it

is changing, and also why these facts are important for anyone who wants to call

themselves a Python professional. This chapter also features the most popular and

canonical ways of working in Python—popular productivity tools and conventions

that are de facto standards now.

Chapter 2, Syntax Best Practices – below the Class Level, presents iterators, generators,

descriptors, and so on, in an advanced way. It also covers useful notes about Python

idioms and internal CPython types implementations with their computational

complexities as a rationale for showcased idioms.

Chapter 3, Syntax Best Practices – above the Class Level, explains syntax best practices,

but focuses above the class level. It covers more advanced object-oriented concepts

and mechanisms available in Python. This knowledge is required in order to

understand the last section of the chapter, which presents different approaches

to metaprogramming in Python.

Chapter 4, Choosing Good Names, involves choosing good names. It is an extension

to PEP 8 with naming best practices, but also gives tips on designing good APIs.

Chapter 5, Writing a Package, explains how to create the Python package and which

tools to use in order to properly distribute it on the ofcial Python Package Index

or any other package repository. Information about packages is supplemented

with a brief review of the tools that allow you to create standalone executables

from Python sources.

Chapter 6, Deploying Code, aims mostly at Python web developers and backend

engineers, because it deals with code deployments. It explains how Python

applications should be built in order to be easily deployed to remote servers and

what tools you can use in order to automate that process. This chapter dovetails

with Chapter 5, Writing a Package, because it shows how packages and private

package repositories can be used to streamline your application deployments.

Chapter 7, Python Extensions in Other Languages, explains why writing C extensions

for Python might be a good solution sometimes. It also shows that it is not as hard

as it seems to be as long as the proper tools are used.

Chapter 8, Managing Code, gives some insight into how a project code base can be

managed and explains how to set up various continuous development processes.

Chapter 9, Documenting Your Project, covers documentation and provides tips on

technical writing and how Python projects should be documented.

Preface

[ xiii ]

Chapter 10, Test-Driven Development, explains the basic principles of test-driven

development and the tools that can be used in this development methodology.

Chapter 11, Optimization – General Principles and Proling Techniques, explains

optimization. It provides proling techniques and an optimization strategy guideline.

Chapter 12, Optimization – Some Powerful Techniques, extends Chapter 11, Optimization

– General Principles and Proling Techniques, by providing some common solutions to

the performance problems that are often found in Python programs.

Chapter 13, Concurrency, introduces the vast topic of concurrency in Python. It explains

what concurrency is, when it might be necessary to write concurrent applications, and

what are the main approaches to concurrency for Python programmers.

Chapter 14, Useful Design Patterns, concludes the book with a set of useful design

patterns and example implementations in Python.

What you need for 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 ofcially

recommended tools. This is why the rst chapter provides a recap of common

utilities (such as virtual environments and pip) that are now considered standard

tools of professional Python developers.

Who this book is for

This book is written for Python developers who wish to go further in mastering

Python. And by developers I mean mostly professionals, so programmers who write

software in Python 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.

It does not mean that hobbyists won't nd anything interesting. This book should be

great for anyone who is interested in learning advance-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 Python 3.5 for those who are still a bit behind

and continue to use Python in version 2.7 or older.

剩余535页未读，继续阅读

泗哥

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