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Python 3 Object-Oriented Programming - Second Edition

You're reading from   Python 3 Object-Oriented Programming - Second Edition Building robust and maintainable software with object oriented design patterns in Python

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Product type Paperback
Published in Aug 2015
Publisher Packt
ISBN-13 9781784398781
Length 460 pages
Edition 1st Edition
Languages
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Author (1):
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Dusty Phillips Dusty Phillips
Author Profile Icon Dusty Phillips
Dusty Phillips
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Table of Contents (15) Chapters Close

Preface 1. Object-oriented Design FREE CHAPTER 2. Objects in Python 3. When Objects Are Alike 4. Expecting the Unexpected 5. When to Use Object-oriented Programming 6. Python Data Structures 7. Python Object-oriented Shortcuts 8. Strings and Serialization 9. The Iterator Pattern 10. Python Design Patterns I 11. Python Design Patterns II 12. Testing Object-oriented Programs 13. Concurrency Index

Comprehensions


Comprehensions are simple, but powerful, syntaxes that allow us to transform or filter an iterable object in as little as one line of code. The resultant object can be a perfectly normal list, set, or dictionary, or it can be a generator expression that can be efficiently consumed in one go.

List comprehensions

List comprehensions are one of the most powerful tools in Python, so people tend to think of them as advanced. They're not. Indeed, I've taken the liberty of littering previous examples with comprehensions and assuming you'd understand them. While it's true that advanced programmers use comprehensions a lot, it's not because they're advanced, it's because they're trivial, and handle some of the most common operations in software development.

Let's have a look at one of those common operations; namely, converting a list of items into a list of related items. Specifically, let's assume we just read a list of strings from a file, and now we want to convert it to a list of...

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