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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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Preface
Who this book is for
What this book covers
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Interaction, scripting, and tools

Python is often described as Batteries Included programming. Everything required is available directly as part of a single download. This provides the runtime, the standard library, and the IDLE editor as a simple development environment.

It's very easy to download and install Python 3.7 and start running it interactively on the desktop. The example in the previous section included the >>> prompt from interactive Python. 

If you're using the Iron Python (IPython) implementation, the interaction will look like this:

In [1]: f = [1, 1, 2, 3]
In [3]: f += [f[-1] + f[-2]]
In [4]: f
Out[4]: [1, 1, 2, 3, 5]

The prompt is slightly different, but the language is the same. Each statement is evaluated as it is presented to Python. 

This is handy for some experimentation. Our goal is to build tools, frameworks, and applications. While many of the examples will be shown in an interactive style, most of the actual programming will be via script files.

Running examples interactively makes a profound statement. Well-written Python code should be simple enough that it can be run from the command line.

Good Python is simple. We should be able to demonstrate a design at the >>> prompt.

Interactive use is not our goal. Exercising code from the >>> prompt is a quality test for complexity. If the code is too complex to exercise it from the >>> prompt, then refactoring is needed.

The focus of this book is on creating complete scripts, modules, packages, and applications. Even though some examples are shown in interactive mode, the objective is to create Python files. These files may be as simple as a script or as complex as a directory with files to create a web application.

Tools such as mypy, pytest, and pylint work with Python files. Preparing script files can be done with almost any text editor. It's best, however, to work with an IDE, where a number of tools can be provided to help develop applications and scripts.

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