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What you will learn

Create applications with flexible logging, powerful configuration and commandline options, automated unit tests, and good documentation

Get to grips with different design patterns for the __init__() method

Design callable objects and context managers

Perform object serialization in formats such as JSON, YAML, Pickle, CSV, and XML

Map Python objects to a SQL database using the builtin 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 commandline arguments and integrate this with configuration files and environment variables

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!

Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!

50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.

Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.

Thousands of reference materials covering every tech concept you need to stay up to date.

Subscribe now

View plans & pricing

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A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

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Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

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Amazon verified reviews

David Jul 01, 2017

A+ thanks!

Amazon Verified review

Z-Car Man Sep 10, 2015

Although I have worked in all areas of the software lifecycle I was new to Python a year ago. When I heard I would be programming in Python I brought a number of books aimed at the intermediate Python programmer. These were expensive and verbose, and failed to hit the mark. How you can write over 1000 pages and skimp some of the fundamentals is beyond me. My original “C” book, Kernigan and Richie, was just over 200 pages and to the point. Word processors have a lot to answer for! My exposure to OO has been limited (C# for a few months and not explained well) and some wxPython. With the project I am now working on I felt I needed a good book but not a door stop. After researching quite a bit I came across this book and felt it was worth buying. At nearly 600 pages it is not a small book but Steven Lott has kept it to the point and relevant throughout. Many authors on software related subjects could learn a lot on how to structure a book from him.The book is broken down into three main sections: Pythonic Classes via Special Methods, Persistence and Serialization and Testing, Debugging, Deploying, and Maintaining. This makes it more manageable. My OO skills in Python have grown markedly in a week. Highly recommended.

Amazon Customer Dec 17, 2016

As represented; no problems

Mike Driscoll May 16, 2014

This is one of Packt’s best books and also one of the best advanced Python books I’ve read. Let’s take a few moments to talk about the chapters. The book is based around the concept of casino Blackjack, which is kind of an odd topic for a programming book. Regardless, the author uses it and a few other examples to help demonstrate some fairly advanced topics in Python. The first chapter is all about Python __init__() method. It shows the reader how to use __init__ in a superclass and a factory function. The second chapter jumps into all of Python’s basic special methods, such as __repr__, __format__, __hash__, etc. You will learn a lot about metaprogramming in these first couple of chapters. Also note that this book is for Python 3 only.Chapter 3 digs into attributes, properties and descriptors. You will learn how to use __slots__, create immutable objects and work with “eagerly computer attributes”. Chapters 4-6 are about creating and working with callables, contexts and containers. There is information about memoization, creating custom callables, how to use __enter__ / __exit__, working with the collections module (deque, ChainMap, OrderedDict, etc) and more! Chapter 7 talks about creating your own Number, which was something I’d never considered doing. The author admits that you normally wouldn’t do it either, but he does teach the reader some interesting concepts (numeric hashes and in-place operators). Chapter 8 finishes up Part 1 with information on decorators and mixins.Part 2 is all about persistence and serialization. Chapter 9 focuses on JSON, YAML and Pickle. The author favors YAML, so you’ll see a lot of examples using it in this section. Chapter 10 digs into using Python shelve objects and using CRUD operations in relation to complex objects. Chapter 11 is about SQLite. Chapter 12 goes into details of using Python to create a REST server and create WSGI applications. Chapter 13 rounds out Part 2 by covering configuration files using Python, JSON, YAML and PLIST.The last section of the book covers testing, debugging, deploying and maintaining. It jumps right in with chapter 14′s topics on the logging and warning modules. Chapter 15 details how to create unittests and doctests in Python. Chapter 16 covers working with command line options via argparse and creating a main() function. In chapter 17, we learn how to design modules and packages. The last chapter of the book goes over quality assurance and documentation. You will learn a bit about the RST markup language and Sphinx for creating documentation.I found Part 1 to be the most interesting part of the book. I learned a great deal about how classes work, metaprogramming techniques and the difference between callables and functions. I think the book is worth purchasing just for that section! Part 2 has a lot of interesting items too, although I question the author’s insistence on using YAML over JSON. I also do not understand why PLIST was even covered as a configuration file type. Part 3 seemed a bit rushed to me. The chapters aren’t as detailed nor the examples as interesting. On the other hand, I may be a bit jaded as this section was mostly material that I already knew. Overall, I found this to be one of the best Python books I’ve read in the last few years. I would definitely recommend it to anyone who wants to learn more about Python’s internals, especially Python’s “magic methods”.

Louis P. Mar 14, 2016

Great content on python classes and some other topics (serialization, etc.). I like a book better than having to google every step or search the documentation. I don't use it anymore but it was a great way to make progress with python.

Mastering Object-oriented Python: If you want to master object-oriented Python programming this book is a must-have. With 750 code samples and a relaxed tutorial, it's a seamless route to programming Python.

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