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Mastering Object-Oriented Python

Mastering Object-Oriented Python - Second Edition

By : Steven F. Lott
3.8 (4)
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Mastering Object-Oriented Python

Mastering Object-Oriented Python

3.8 (4)
By: Steven F. Lott

Overview of this book

Object-oriented programming (OOP) is a relatively complex discipline to master, and it can be difficult to see how general principles apply to each language's unique features. With the help of the latest edition of Mastering Objected-Oriented Python, you'll be shown how to effectively implement OOP in Python, and even explore Python 3.x. Complete with practical examples, the book guides you through the advanced concepts of OOP in Python, and demonstrates how you can apply them to solve complex problems in OOP. You will learn how to create high-quality Python programs by exploring design alternatives and determining which design offers the best performance. Next, you'll work through special methods for handling simple object conversions and also learn about hashing and comparison of objects. As you cover later chapters, you'll discover how essential it is to locate the best algorithms and optimal data structures for developing robust solutions to programming problems with minimal computer processing. Finally, the book will assist you in leveraging various Python features by implementing object-oriented designs in your programs. By the end of this book, you will have learned a number of alternate approaches with different attributes to confidently solve programming problems in Python.
Table of Contents (25 chapters)
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Section 1: Tighter Integration Via Special Methods
11
Section 2: Object Serialization and Persistence
17
Section 3: Object-Oriented Testing and Debugging

Using ChainMap for defaults and overrides

We'll often have a configuration file hierarchy. Previously, we listed several locations where configuration files can be installed. The configparser module, for example, is designed to read a number of files in a particular order and integrate the settings by having later files override values from earlier files.

We can implement elegant default-value processing using the collections.ChainMap class. You can refer to Chapter 7, Creating Containers and Collections for some background on this class. We'll need to keep the configuration parameters as dict instances, which is something that works out well using exec() to evaluate Python-language initialization files.

Using this will require us to design our configuration parameters as a flat dictionary of values. This may be a bit of a burden for applications with a large number...

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