Table of Contents
Acknowledgments xv
Introduction 1
Who Should Read This Book And Why 2
About This Book 2
1 Starting Your Project 5
Versions of Python 5
Laying Out Your Project 7
What to Do 7
What Not to Do 8
Version Numbering 8
Coding Style and Automated Checks 10
Tools to Catch Style Errors 11
Tools to Catch Coding Errors 12
Joshua Harlow on Python 13
2 Modules, Libraries, And Frameworks 15
The Import System 16
The sys Module 17
Import Paths 18
Custom Importers 18
Meta Path Finders 19
Useful Standard Libraries 20
External Libraries 22
The External Libraries Safety Checklist 23
Protecting Your Code With an API Wrapper 23
Package Installation: Getting More from pip 24
Using and Choosing Frameworks 26
Doug Hellmann, Python Core Developer, on Python Libraries 27
3 Documentation And Good API Practice
Documenting with Sphinx 34
Getting Started with Sphinx and Rest 35
Sphinx Modules 36
Writing a Sphinx Extension 39
Managing Changes to YOUR APIs 40
Numbering API Versions 41
Documenting Your API Changes 41
Marking Deprecated Functions with the warnings Module 43
Summary 45
Christophe de Vienne on Developing APIs 45
4 Handling Timestamps And Time Zones 49
The Problem of Missing Time Zones 50
Building Default datetime Objects 50
Time Zone-Aware Timestamps with dateutil 52
Serializing Time Zone-Aware datetime Objects 54
Solving Ambiguous Times 55
Summary 56
5 Distributing Your Software 57
A Bit of setup.py History 58
Packaging with setup.cfg 60
The Wheel Format Distribution Standard 61
Sharing Your Work with the World 64
Entry Points 67
Visualizing Entry Points 68
Using Console Scripts 69
Using Plugins and Drivers 71
Summary 73
Nick Coghlan on Packaging 74
6 Unit Testing 75
The Basics of Testing 76
Some Simple Tests 76
Skipping Tests 78
Running Particular Tests 79
Running Tests in Parallel 81
Creating Objects Used in Tests with Fixtures 81
Running Test Scenarios 83
Controlled Tests Using Mocking 84
Revealing Untested Code with coverage 88
Virtual Environments 90
Setting Up a Virtual Environment 91
Using virtualenv with tox 92
Re-creating an Environment 94
Using Different Python Versions 95
Integrating Other Tests 95
Testing Policy 96
Robert Collins on Testing 97
7 Methods And Decorators 99
Decorators and When to Use Them 100
Creating Decorators 100
Writing Decorators 101
Stacking Decorators 102
Writing Class Decorators 103
How Methods Work in Python 107
Static Methods 108
Class Methods 109
Abstract Methods 110
Mixing Static, Class, and Abstract Methods 112
Putting Implementations in Abstract Methods 114
The Truth About super 114
Summary 117
8 Functional Programming 119
Creatinq Pure Functions 120
Generators 121
Creating a Generator 121
Returning and Passing Values with yield 123
Inspecting Generators 124
List Comprehensions 125
Functional Functions Functioning 126
Applying Functions to Items with map() 127
Filtering Lists with filter() 127
Getting Indexes with enumerate() 127
Sorting a List with sorted() 128
Finding Items That Satisfy Conditions with any() and all() 128
Combining Lists with zip() 129
A Common Problem Solved 129
Useful itertools Functions 132
Summary 134
9 The Abstract Syntax Tree, HY, And Lisp-Like Attributes 135
Looking at the AST 136
Writing a Program Using the AST 137
The AST Objects 138
Walking Through an AST 139
Extending flake8 with AST Checks 140
Writing the Class 141
Ignoring Irrelevant Code 141
Checking for the Correct Decorator 142
Looking for self 143
A Quick Introduction to Hy 145
Summary 147
Paul Tagliamonte on the AST and Hy 147
10 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
11 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
12 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
13 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
