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Mastering Object-oriented Python


For those who know the basics of object-oriented Python this book is a must-have. With 750 code samples and a relaxed tutorial approach, it’s the seamless route to more sophisticated programming.


  • 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


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.

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