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Wednesday, August 10, 2011

Expert Python Programming






Table of Contents
Preface 1
Chapter 1: Getting started 9
Installing Python 10
Python Implementations 10
Jython 10
IronPython 11
PyPy 11
Other Implementations 11
Linux Installation 12
Package Installation 12
Compiling the Sources 13
Windows Installation 14
Installing Python 14
Installing MinGW 15
Installing MSYS 16
Mac OS X Installation 17
Package Installation 17
Compiling the Source 18
The Python Prompt 18
Customizing the Interactive Prompt 19
iPython: An Advanced Prompt 20
Installing setuptools 21
Understanding How It Works 21
setuptools Installation Using EasyInstall 22
Hooking MinGW into distutils 23
Working Environment 24
Using an Editor and Complementary Tools 24
Code Editor 25
Installing and Configuring Vim 25
Using Another Editor 27
Extra Binaries 28
Using an Integrated Development Environment 28
Installing Eclipse with PyDev 29
Summary 32
Chapter 2: Syntax Best Practices—Below the Class Level 33
List Comprehensions 34
Iterators and Generators 36
Generators 37
Coroutines 41
Generator Expressions 43
The itertools Module 44
islice: The Window Iterator 44
tee: The Back and Forth Iterator 45
groupby: The uniq Iterator 45
Other Functions 46
Decorators 47
How to Write a Decorator 48
Argument checking 50
Caching 52
Proxy 54
Context Provider 55
with and contextlib 56
The contextlib Module 58
Context Example 59
Summary 61
Chapter 3: Syntax Best Practices—Above the Class Level 63
Subclassing Built-in Types 63
Accessing Methods from Superclasses 65
Understanding Python's Method Resolution Order (MRO) 66
super Pitfalls 70
Mixing super and classic Calls 70
Heterogeneous Arguments 72
Best Practices 73
Descriptors and Properties 74
Descriptors 74
Introspection Descriptor 77
Meta-descriptor 79
Properties 81
Slots 83
Meta-programming 84
The__new__ Method 84
__metaclass__ Method 86
Summary 89
Chapter 4: Choosing Good Names 91
PEP 8 and Naming Best Practices 91
Naming Styles 92
Variables 92
Constants 92
Public and Private Variables 95
Functions and Methods 96
The Private Controversy 97
Special Methods 98
Arguments 98
Properties 99
Classes 99
Modules and Packages 99
Naming Guide 100
Use "has" or "is" Prefix for Boolean Elements 100
Use Plural for Elements That Are Sequences 100
Use Explicit Names for Dictionaries 101
Avoid Generic Names 101
Avoid Existing Names 101
Best Practices for Arguments 102
Build Arguments by Iterative Design 102
Trust the Arguments and Your Tests 103
Use *args and **kw Magic Arguments Carefully 104
Class Names 106
Module and Package Names 107
Working on APIs 107
Tracking Verbosity 108
Building the Namespace Tree 108
Splitting the Code 110
Using Eggs 111
Using a Deprecation Process 112
Useful Tools 113
Pylint 113
CloneDigger 115
Summary 116
Chapter 5: Writing a Package 117
A Common Pattern for All Packages 117
setup.py, the Script That Controls Everything 118
sdist 119
build and bdist 121
bdist_egg 122
install 123
How to Uninstall a Package 123
develop 124
test 124
register and upload 125
Creating a New Command 128
setup.py Usage Summary 129
Other Imprtant Metadata 129
The Template-Based Approach 131
Python Paste 131
Creating Templates 133
Creating the Package Template 133
Development Cycle 138
Summary 141
Chapter 6: Writing an Application 143
Atomisator: An Introduction 143
Overall Picture 144
Working Environment 146
Adding a Test Runner 148
Adding a packages Structure 148
Writing the Packages 149
atomisator.parser 149
Creating the Initial Package 150
Creating the Initial doctest 151
Building the Test Environment 153
Writing the Code 153
atomisator.db 154
SQLAlchemy 154
Providing the APIs 158
atomisator.feed 159
atomisator.main 160
Distributing Atomisator 162
Dependencies between Packages 164
Summary 165
Chapter 7: Working with zc.buildout 167
zc.buildout Philosophy 168
Configuration File Structure 168
Minimum Configuration File 169
[buildout] Section Options 169
The buildout Command 170
Recipes 172
Notable Recipes 174
Creating Recipes 174
Atomisator buildout Environment 175
buildout Folder Structure 176
Going Further 177
Releasing and Distributing 178
Releasing the Packages 178
Adding a Release Configuration File 179
Building and Releasing the Application 180
Summary 181
Chapter 8: Managing Code 183
Version Control Systems 183
Centralized Systems 184
Distributed Systems 186
Distributed Strategies 188
Centralized or Distributed? 188
Mercurial 189
Project Management with Mercurial 193
Setting Up a Dedicated Folder 193
Configuring hgwebdir 194
Configuring Apache 195
Setting Up Authorizations 198
Setting Up the Client Side 199
Continuous Integration 200
Buildbot 201
Installing Buildbot 202
Hooking Buildbot and Mercurial 204
Hooking Apache and Buildbot 205
Summary 206
Chapter 9: Managing Life Cycle 207
Different Approaches 207
Waterfall Development Model 207
Spiral Development Model 208
Iterative Development Model 210
Defining a Life Cycle 210
Planning 212
Development 212
Global Debug 212
Release 213
Setting Up a Tracking System 213
Trac 213
Installation 215
Apache Settings 217
Permission Settings 218
Project Life Cycle with Trac 219
Planning 219
Development 221
Cleaning 221
Release 221
Summary 222
Chapter 10: Documenting Your Project 223
The Seven Rules of Technical Writing 223
Write in Two Steps 224
Target the Readership 225
Use a Simple Style 226
Limit the Scope of the Information 227
Use Realistic Code Examples 227
Use a Light but Sufficient Approach 228
Use Templates 228
A reStructuredText Primer 229
Section Structure 230
Lists 232
Inline Markup 232
Literal Block 232
Links 233
Building the Documentation 234
Building the Portfolio 234
Design 235
Usage 238
Operations 242
Make Your Own Portfolio 242
Building the Landscape 243
Producer's Layout 243
Consumer's Layout 244
Summary 249
Chapter 11: Test-Driven Development 251
I Don't Test 251
Test-Driven Development Principles 251
Preventing Software Regression 253
Improving Code Quality 254
Providing the Best Developer Documentation 254
Producing Robust Code Faster 255
What Kind of Tests? 255
Acceptance Tests 255
Unit Tests 256
Python Standard Test Tools 256
I Do Test 260
Unittest Pitfalls 260
Unittest Alternatives 261
nose 262
py.test 264
Fakes and Mocks 267
Building a Fake 268
Using Mocks 271
Document-Driven Development 273
Writing a Story 273
Summary 274
Chapter 12: Optimization: General Principles and Profiling
Techniques 275
The Three Rules of Optimization 275
Make It Work First 275
Work from the User's Point of View 276
Keep the Code Readable(and thus maintainable) 277
Optimization Strategy 277
Find Another Culprit 278
Scale the Hardware 278
Write a Speed Test 279
Finding Bottlenecks 280
Profiling CPU Usage 280
Macro-Profiling 280
Micro-Profiling 284
Measuring Pystones 287
Profiling Memory Usage 288
How Python Deals with Memory 288
Profiling Memory 290
Profiling Network Usage 295
Summary 296
Chapter 13: Optimization: Solutions 297
Reducing the Complexity 298
Measuring Cyclomatic Complexity 298
Measuring the Big-O Notation 298
Simplifying 301
Searching in a List 301
Using a Set Instead of a List 302
Cut the External Calls, Reduce the Workload 303
Using Collections 303
Multithreading 306
What is Multithreading? 307
How Python Deals with Threads 307
When Should Threading Be Used? 309
Building Responsive Interfaces 309
Delegating Work 309
Multi-User Applications 310
Simple Example 310
Multiprocessing 314
Pyprocessing 315
Caching 317
Deterministic Caching 318
Non-Deterministic Caching 321
Pro-Active Caching 322
Memcached 322
Summary 323
Chapter 14: Useful Design Patterns 325
Creational Patterns 325
Singleton 326
Structural Patterns 328
Adapter 329
Interfaces 331
Proxy 332
Facade 333
Behavioral Patterns 334
Observer 334
Visitor 336
Template 339
Summary 341
Index 343

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