CONTENTS IN DETAIL

ACKNOWLEDGMENTS

INTRODUCTION

Who Should Read This Book and Why

About This Book

1
STARTING YOUR PROJECT

Versions of Python

Laying Out Your Project

What to Do

What Not to Do

Version Numbering

Coding Style and Automated Checks

Tools to Catch Style Errors

Tools to Catch Coding Errors

Joshua Harlow on Python

2
MODULES, LIBRARIES, AND FRAMEWORKS

The Import System

The sys Module

Import Paths

Custom Importers

Meta Path Finders

Useful Standard Libraries

External Libraries

The External Libraries Safety Checklist

Protecting Your Code with an API Wrapper

Package Installation: Getting More from pip

Using and Choosing Frameworks

Doug Hellmann, Python Core Developer, on Python Libraries

3
DOCUMENTATION AND GOOD API PRACTICE

Documenting with Sphinx

Getting Started with Sphinx and reST

Sphinx Modules

Writing a Sphinx Extension

Managing Changes to Your APIs

Numbering API Versions

Documenting Your API Changes

Marking Deprecated Functions with the warnings Module

Summary

Christophe de Vienne on Developing APIs

4
HANDLING TIMESTAMPS AND TIME ZONES

The Problem of Missing Time Zones

Building Default datetime Objects

Time Zone–Aware Timestamps with dateutil

Serializing Time Zone–Aware datetime Objects

Solving Ambiguous Times

Summary

5
DISTRIBUTING YOUR SOFTWARE

A Bit of setup.py History

Packaging with setup.cfg

The Wheel Format Distribution Standard

Sharing Your Work with the World

Entry Points

Visualizing Entry Points

Using Console Scripts

Using Plugins and Drivers

Summary

Nick Coghlan on Packaging

6
UNIT TESTING

The Basics of Testing

Some Simple Tests

Skipping Tests

Running Particular Tests

Running Tests in Parallel

Creating Objects Used in Tests with Fixtures

Running Test Scenarios

Controlled Tests Using Mocking

Revealing Untested Code with coverage

Virtual Environments

Setting Up a Virtual Environment

Using virtualenv with tox

Re-creating an Environment

Using Different Python Versions

Integrating Other Tests

Testing Policy

Robert Collins on Testing

7
METHODS AND DECORATORS

Decorators and When to Use Them

Creating Decorators

Writing Decorators

Stacking Decorators

Writing Class Decorators

How Methods Work in Python

Static Methods

Class Methods

Abstract Methods

Mixing Static, Class, and Abstract Methods

Putting Implementations in Abstract Methods

The Truth About super

Summary

8
FUNCTIONAL PROGRAMMING

Creating Pure Functions

Generators

Creating a Generator

Returning and Passing Values with yield

Inspecting Generators

List Comprehensions

Functional Functions Functioning

Applying Functions to Items with map()

Filtering Lists with filter()

Getting Indexes with enumerate()

Sorting a List with sorted()

Finding Items That Satisfy Conditions with any() and all()

Combining Lists with zip()

A Common Problem Solved

Useful itertools Functions

Summary

9
THE ABSTRACT SYNTAX TREE, HY, AND LISP-LIKE ATTRIBUTES

Looking at the AST

Writing a Program Using the AST

The AST Objects

Walking Through an AST

Extending flake8 with AST Checks

Writing the Class

Ignoring Irrelevant Code

Checking for the Correct Decorator

Looking for self

A Quick Introduction to Hy

Summary

Paul Tagliamonte on the AST and Hy

10
PERFORMANCES AND OPTIMIZATIONS

Data Structures

Understanding Behavior Through Profiling

cProfile

Disassembling with the dis Module

Defining Functions Efficiently

Ordered Lists and bisect

namedtuple and Slots

Memoization

Faster Python with PyPy

Achieving Zero Copy with the Buffer Protocol

Summary

Victor Stinner on Optimization

11
SCALING AND ARCHITECTURE

Multithreading in Python and Its Limitations

Multiprocessing vs. Multithreading

Event-Driven Architecture

Other Options and asyncio

Service-Oriented Architecture

Interprocess Communication with ZeroMQ

Summary

12
MANAGING RELATIONAL DATABASES

RDBMSs, ORMs, and When to Use Them

Database Backends

Streaming Data with Flask and PostgreSQL

Writing the Data-Streaming Application

Building the Application

Dimitri Fontaine on Databases

13
WRITE LESS, CODE MORE

Using six for Python 2 and 3 Support

Strings and Unicode

Handling Python Modules Moves

The modernize Module

Using Python Like Lisp to Make a Single Dispatcher

Creating Generic Methods in Lisp

Generic Methods with Python

Context Managers

Less Boilerplate with attr

Summary

INDEX