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Mastering Object-Oriented Python

Mastering Object-Oriented Python

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

The __bytes__() method

There are relatively few occasions when you will need to transform an object into bytes. Bytes representation is used for the serialization of objects for persistent storage or transfer. We'll look at this in detail in Chapter 10, Serializing and Saving - JSON, YAML, Pickle, CSV and XML through Chapter 14, Configuration Files and Persistence.

In the most common situation, an application will create a string representation, and the built-in encoding capabilities of the Python IO classes can be used to transform the string into bytes. This works perfectly for almost all situations. The main exception would be when we're defining a new kind of string. In which case, we'd need to define the encoding of that string.

The bytes() function does a variety of things, depending on the arguments:

  • bytes(integer): This returns an immutable bytes object...
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