Python高效编程秘籍：实战技巧与Python 3优化

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"《Effective Python》（第二版）是一本备受推崇的Python编程经典教材，专为提升代码效率、实现目标和编写简洁代码而设计。本书在2015年首版的基础上进行了更新和扩展，适用于Python 3环境，无论编程经验丰富的专业人士还是初学者都能从中受益匪浅。该书得到了众多业界知名人士的高度评价。Wes McKinney，Python Pandas项目的创始人和Ursa Labs的总监，热烈推荐这本书，认为它是跨语言程序员深入了解Python独特特性的权威指南。即使对于资深的Python开发者，如Simon Willison，他在使用Python近二十年后仍然能从书中学习到许多实用技巧，特别是关于Python 3新功能的运用。《Effective Python》充满了实战建议，帮助我们理解社区中所说的“Pythonic”编程风格。书中不仅涵盖了如何让Python代码运行得更快，比如介绍如何使用`bisect`对排序列表进行高效搜索，还关注代码可读性和错误预防。例如，通过强制使用关键字参数，可以简化函数调用并减少出错可能性。此外，作者还分享了各种优化技术，使读者能够改进代码性能，提高代码质量。《Effective Python》是一本不可或缺的参考书籍，无论是对Python新手还是寻求提升的专业人员，都能提供实用的编程策略和最佳实践，助你在Python编程旅程中不断进步。"

Preface

The Python programming language has unique strengths and charms

that can be hard to grasp. Many programmers familiar with other

languages often approach Python from a limited mindset instead of

embracing its full expressivity. Some programmers go too far in the

other direction, overusing Python features that can cause big prob-

lems later.

This book provides insight into the Pythonic way of writing programs:

the best way to use Python. It builds on a fundamental understanding

of the language that I assume you already have. Novice programmers

will learn the best practices of Python’s capabilities. Experienced pro-

grammers will learn how to embrace the strangeness of a new tool

with confidence.

My goal is to prepare you to make a big impact with Python.

What This Book Covers

Each chapter in this book contains a broad but related set of items.

Feel free to jump between items and follow your interest. Each item

contains concise and specific guidance explaining how you can write

Python programs more effectively. Items include advice on what to

do, what to avoid, how to strike the right balance, and why this is the

best choice. Items reference each other to make it easier to fill in the

gaps as you read.

This second edition of this book is focused exclusively on Python 3

(see Item 1: “Know Which Version of Python You’re Using”), up to and

including version 3.8. Most of the original items from the first edi-

tion have been revised and included, but many have undergone sub-

stantial updates. For some items, my advice has completely changed

between the two editions of the book due to best practices evolving as

Python has matured. If you’re still primarily using Python 2, despite

xviii Preface

its end-of-life on January 1st, 2020, the previous edition of the book

may be more useful to you.

Python takes a “batteries included” approach to its standard library,

in comparison to many other languages that ship with a small

number of common packages and require you to look elsewhere

for important functionality. Many of these built-in packages are so

closely intertwined with idiomatic Python that they may as well be

part of the language specification. The full set of standard modules

is too large to cover in this book, but I’ve included the ones that I feel

are critical to be aware of and use.

Chapter 1: Pythonic Thinking

The Python community has come to use the adjective Pythonic to

describe code that follows a particular style. The idioms of Python

have emerged over time through experience using the language and

working with others. This chapter covers the best way to do the most

common things in Python.

Chapter 2: Lists and Dictionaries

In Python, the most common way to organize information is in a

sequence of values stored in a list. A list’s natural complement is the

dict that stores lookup keys mapped to corresponding values. This

chapter covers how to build programs with these versatile building

blocks.

Chapter 3: Functions

Functions in Python have a variety of extra features that make a

programmer’s life easier. Some are similar to capabilities in other pro-

gramming languages, but many are unique to Python. This chapter

covers how to use functions to clarify intention, promote reuse, and

reduce bugs.

Chapter 4: Comprehensions and Generators

Python has special syntax for quickly iterating through lists, dictio-

naries, and sets to generate derivative data structures. It also allows

for a stream of iterable values to be incrementally returned by a

function. This chapter covers how these features can provide better

performance, reduced memory usage, and improved readability.

Chapter 5: Classes and Interfaces

Python is an object-oriented language. Getting things done in Python

often requires writing new classes and defining how they interact

xx Preface

when they wrap. I truncate some snippets with ellipses (... ) to indi-

cate regions where code exists that isn’t essential for expressing the

point. You’ll need to download the full example code (see below on

where to get it) to get these truncated snippets to run correctly on

your computer.

I take some artistic license with the Python style guide in order to

make the code examples better fit the format of a book, or to highlight

the most important parts. I’ve also left out embedded documentation

to reduce the size of code examples. I strongly suggest that you don’t

emulate this in your projects; instead, you should follow the style

guide (see Item 2: “Follow the PEP 8 Style Guide”) and write documen-

tation (see Item 84: “Write Docstrings for Every Function, Class, and

Module”).

Most code snippets in this book are accompanied by the correspond-

ing output from running the code. When I say “output,” I mean console

or terminal output: what you see when running the Python program

in an interactive interpreter. Output sections are in monospace font

and are preceded by a >>> line (the Python interactive prompt). The

idea is that you could type the code snippets into a Python shell and

reproduce the expected output.

Finally, there are some other sections in monospace font that are not

preceded by a >>> line. These represent the output of running pro-

grams besides the normal Python interpreter. These examples often

begin with $ characters to indicate that I’m running programs from a

command-line shell like Bash. If you’re running these commands on

Windows or another type of system, you may need to adjust the pro-

gram names and arguments accordingly.

Where to Get the Code and Errata

It’s useful to view some of the examples in this book as whole

programs without interleaved prose. This also gives you a chance to

tinker with the code yourself and understand why the program works

as described. You can find the source code for all code snippets in

this book on the book’s website at https://effectivepython.com. The

website also includes any corrections to the book, as well as how to

report errors.

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