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Python Essentials

You're reading from   Python Essentials Modernize existing Python code and plan code migrations to Python using this definitive guide

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Product type Paperback
Published in Jun 2015
Publisher Packt
ISBN-13 9781784390341
Length 298 pages
Edition 1st Edition
Languages
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Author (1):
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Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
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Table of Contents (17) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Simple Data Types 3. Expressions and Output 4. Variables, Assignment and Scoping Rules 5. Logic, Comparisons, and Conditions 6. More Complex Data Types 7. Basic Function Definitions 8. More Advanced Functions 9. Exceptions 10. Files, Databases, Networks, and Contexts 11. Class Definitions 12. Scripts, Modules, Packages, Libraries, and Applications 13. Metaprogramming and Decorators 14. Fit and Finish – Unit Testing, Packaging, and Documentation 15. Next Steps Index

Preface

Python programming should be expressive and elegant. In order for this to be true, the language itself must be easy to learn and easy to use. Any practical language—and its associated libraries—can present a daunting volume of information. In order to help someone learn Python, we've identified and described those features that seem essential.

Learning a language can be a long voyage. We'll pass numerous islands, archipelagos, inlets, and estuaries along the route. Our objective is to point out the key features that will be passed during the initial stages of this journey.

The concepts of data structures and algorithms are ever-present considerations in programming. Our overall approach is to introduce the various Python data structures first. As part of working with a given class of objects, the language statements are introduced later. One of Python's significant advantages over other languages is the rich collection of built-in data types. Selecting an appropriate representation of data can lead to elegant, high-performance applications.

An essential aspect of Python is its overall simplicity. There are very few operators and very few different kinds of statements. Much of the code we write can be generic with respect to the underlying data type. This allows us to easily exchange different data structure implementations as part of making tradeoffs between storage, performance, accuracy, and other considerations.

Some subject areas could take us well beyond the basics. Python's object-oriented programming features are rich enough to easily fill several large volumes. If we're also interested in functional programming features, we can study these in far more depth elsewhere. We'll touch only briefly on these subjects.

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