掌握Python编程精华：第二版

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"《Expert Python Programming 第二版》是一本专为Python开发者设计的专业指南，作者Michał Jaworski和Tarek Ziadé凭借多年的编程经验，分享了在Python 3.5环境下构建各种应用的最佳实践和高级概念。本书不仅深入探讨了Python语言本身，更侧重于工具和技术的应用，旨在帮助读者成为精通Python的高级程序员。书中内容涵盖了从简短的几小时系统脚本到大型项目开发的广泛实践经验，读者可以学习到如何有效地利用Python进行高效、模块化和可维护的代码编写。它强调了编码规范、代码优化、版本控制、测试、调试以及团队协作等关键技能，这些都是现代软件开发过程中不可或缺的部分。此外，该书遵循版权法规定，所有内容未经出版商Packt Publishing事先书面许可，不得复制、存储或任何形式传输。尽管本书力求准确，但并不保证所有信息无误，也不承担因使用本书信息导致的直接或间接损失的责任。作者和出版社尽力确保商标使用正确，但在某些情况下，由于篇幅限制，可能未能提及所有的公司和产品名称。总体而言，《Expert Python Programming 第二版》是一本实用且全面的资源，适合那些希望提升Python编程技能，或者需要深入了解高级开发流程的读者，无论是初学者还是经验丰富的开发者都能从中受益匪浅。"

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

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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.

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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.

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