Serious Python：专家级编程技巧与实战指南

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PERFORMANCES AND OPTIMIZATIONS 151

Data Structures .................................................. 152

Understanding Behavior Through Profiling................................ 154

cProfile ................................................ 154

Disassembling with the dis Module ............................. 156

Defining Functions Efficiently . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158

Ordered Lists and bisect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159

namedtuple and Slots .............................................. 162

Memoization .................................................... 167

Faster Python with PyPy............................................. 169

Achieving Zero Copy with the Buffer Protocol ............................. 170

Summary ...................................................... 174

Victor Stinner on Optimization........................................ 174

SCALING AND ARCHITECTURE 177

Multithreading in Python and Its Limitations ............................... 178

Multiprocessing vs. Multithreading ..................................... 179

Event-Driven Architecture............................................ 181

Other Options and asyncio .......................................... 182

Service-Oriented Architecture......................................... 184

Interprocess Communication with ZeroMQ ............................... 185

Summary ...................................................... 186

MANAGING RELATIONAL DATABASES 187

RDBMSs, ORMs, and When to Use Them ................................ 187

Database Backends ............................................... 190

Streaming Data with Flask and PostgreSQL ............................... 190

Writing the Data-Streaming Application.......................... 191

Building the Application..................................... 193

Dimitri Fontaine on Databases ........................................ 195

WRITE LESS, CODE MORE 201

Using six for Python 2 and 3 Support ................................... 201

Strings and Unicode ....................................... 202

Handling Python Modules Moves .............................. 203

The modernize Module ..................................... 203

Using Python Like Lisp to Make a Single Dispatcher ......................... 203

Creating Generic Methods in Lisp .............................. 204

Generic Methods with Python ................................ 205

Context Managers ................................................ 207

Less Boilerplate with attr ............................................ 210

Summary ...................................................... 213

INDEX 215

2 Introduction

efﬁcient, and scalable to the needs of whatever cloud computing applica-

tion its users require. When you have a project of this size, things like test-

ing and documentation absolutely require automation, or else they won’t

get done at all.

I thought I knew a lot about Python before working on projects of this

scale—a scale I could hardly imagine when I started out—but I’ve learned

a lot more. I’ve also had the opportunity to meet some of the best Python

hackers in the industry and learn from them. They’ve taught me everything

from general architecture and design principles to various helpful tips and

tricks. Through this book, I hope to share the most important things I’ve

learned so that you can build better Python programs—and build them

more efﬁciently, too!

The ﬁrst version of this book, The Hacker’s Guide to Python, came out

in 2014. Now Serious Python is the fourth edition, with updated and entirely

new contents. I hope you enjoy it!

Who Should Read This Book and Why

This book is intended for Python coders and developers who want to take

their Python skills to the next level.

In it, you’ll ﬁnd methods and advice that will help you get the most

out of Python and build future-proof programs. If you’re already working

on a project, you’ll be able to apply the techniques discussed right away to

improve your current code. If you’re starting your ﬁrst project, you’ll be

able to create a blueprint with the best practice.

I’ll introduce you to some Python internals to give you a better under-

standing of how to write efﬁcient code. You will gain a greater insight into

the inner workings of the language that will help you understand problems

or inefﬁciencies.

The book also provides applicable battle-tested solutions to problems

such as testing, porting, and scaling Python code, applications, and libraries.

This will help you avoid making the mistakes that others have made and dis-

cover strategies that will help you maintain your software in the long run.

About This Book

This book is not necessarily designed to be read from front to back. You

should feel free to skip to sections that interest you or are relevant to your

work. Throughout the book, you’ll ﬁnd a wide range of advice and practical

tips. Here’s a quick breakdown of what each chapter contains.

Chapter 1 provides guidance about what to consider before you under-

take a project, with advice on structuring your project, numbering versions,

setting up automated error checking, and more. At the end there’s an inter-

view with Joshua Harlow.

Chapter 2 introduces Python modules, libraries, and frameworks and

talks a little about how they work under the hood. You’ll ﬁnd guidance on

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