Mastering Object-oriented Python (repost)

Grasp the intricacies of object-oriented programming in Python in order to efficiently build powerful real-world applications

Overview
Create applications with flexible logging, powerful configuration and command-line options, automated unit tests, and good documentation.
Use the Python special methods to integrate seamlessly with built-in features and the standard library
Design classes to support object persistence in JSON, YAML, Pickle, CSV, XML, Shelve, and SQL

In Detail

This practical example-oriented guide will teach you advanced concepts of object-oriented programming in Python. This book will present detailed examples of almost all of the special method names that support creating classes that integrate seamlessly with Python's built-in features. It will show you how to use JSON, YAML, Pickle, CSV, XML, Shelve, and SQL to create persistent objects and transmit objects between processes. The book also covers logging, warnings, unit testing, configuration files, and how to work with the command line.

This book is broken into three major parts: Pythonic Classes via Special Methods; Persistence and Serialization; Testing, Debugging, Deploying, and Maintaining. The special methods are broken down into several focus areas: initialization, basics, attribute access, callables, contexts, containers, collections, numbers, and more advanced techniques such as decorators and mixin classes.

What you will learn from this book
Understand the different design patterns for the __init__() method
Discover the essential features of Python 3's abstract base classes and how you can use them for your own applications
Design callable objects and context managers that leverage the with statement
Perform object serialization in formats such as JSON, YAML, Pickle, CSV, and XML
Employ the Shelve module as a sophisticated local database
Map Python objects to a SQL database using the built-in SQLite module
Transmit Python objects via RESTful web services
Devise strategies for automated unit testing, including how to use the doctest and the unittest.mock module
Parse command-line arguments and integrate this with configuration files and environment variables

Approach

This book follows a standard tutorial approach with approximately 750 code samples spread through the 19 chapters. This amounts to over 5,900 lines of code that illustrate each concept.