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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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1
Section 1: Tighter Integration Via Special Methods
11
Section 2: Object Serialization and Persistence
17
Section 3: Object-Oriented Testing and Debugging

Designing callables

There are two easy and commonly-used ways to create callable objects in Python, which are as follows:

  • By using the def statement to create a function.
  • By creating an instance of a class that implements the _call()_ method. This can be done by using collections.abc.Callable as its base class.

Beyond these two, we can also assign a lambda form to a variable. A lambda is a small, anonymous function that consists of exactly one expression. We'd rather not emphasize saving lambdas in a variable, as this leads to the confusing situation where we have a function-like callable that's not defined with a def statement.

The following is a simple callable object, pow1, created from a class:

from typing import Callable
IntExp = Callable[[int, int], int]
class Power1:
def __call__(self, x: int, n: int) -> int:
p = 1
for i in range(n):
...

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