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Python 3 Object-Oriented Programming

Python 3 Object-Oriented Programming

By : Dusty Phillips
4.3 (30)
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Python 3 Object-Oriented Programming

Python 3 Object-Oriented Programming

4.3 (30)
By: Dusty Phillips

Overview of this book

Object-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. This third edition of Python 3 Object-Oriented Programming fully explains classes, data encapsulation, and exceptions with an emphasis on when you can use each principle to develop well-designed software. Starting with a detailed analysis of object-oriented programming, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. You will learn how to create maintainable applications by studying higher level design patterns. The book will show you the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems, unittest and pytest, will be introduced in this book. You'll get a comprehensive introduction to Python's concurrent programming ecosystem. By the end of the book, you will have thoroughly learned object-oriented principles using Python syntax and be able to create robust and reliable programs confidently.
Table of Contents (15 chapters)
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AsyncIO

AsyncIO is the current state of the art in Python concurrent programming. It combines the concept of futures and an event loop with the coroutines we discussed in Chapter 9, The Iterator Pattern. The result is about as elegant and easy to understand as it is possible to get when writing concurrent code, though that isn't saying a lot!

AsyncIO can be used for a few different concurrent tasks, but it was specifically designed for network I/O. Most networking applications, especially on the server side, spend a lot of time waiting for data to come in from the network. This can be solved by handling each client in a separate thread, but threads use up memory and other resources. AsyncIO uses coroutines as a sort of lightweight thread.

The library provides its own event loop, obviating the need for the several lines long the while loop in the previous example. However...

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