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Mastering Object-oriented Python

You're reading from   Mastering Object-oriented Python If you want to master object-oriented Python programming this book is a must-have. With 750 code samples and a relaxed tutorial, it's a seamless route to programming Python.

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Product type Paperback
Published in Apr 2014
Publisher Packt
ISBN-13 9781783280971
Length 634 pages
Edition 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 (26) Chapters Close

Mastering Object-oriented Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Some Preliminaries
1. The __init__() Method FREE CHAPTER 2. Integrating Seamlessly with Python Basic Special Methods 3. Attribute Access, Properties, and Descriptors 4. The ABCs of Consistent Design 5. Using Callables and Contexts 6. Creating Containers and Collections 7. Creating Numbers 8. Decorators and Mixins – Cross-cutting Aspects 9. Serializing and Saving – JSON, YAML, Pickle, CSV, and XML 10. Storing and Retrieving Objects via Shelve 11. Storing and Retrieving Objects via SQLite 12. Transmitting and Sharing Objects 13. Configuration Files and Persistence 14. The Logging and Warning Modules 15. Designing for Testability 16. Coping With the Command Line 17. The Module and Package Design 18. Quality and Documentation Index

Chapter 9. Serializing and Saving – JSON, YAML, Pickle, CSV, and XML

To make a Python object persistent, we must convert it to bytes and write the bytes to a file. We'll call this serialization; it is also called marshaling, deflating or encoding. We'll look at several ways to convert a Python object to a string or a stream of bytes.

Each of these serialization schemes can also be called a physical data format. Each format offers some advantages and disadvantages. There's no best format to represent the objects. We must distinguish a logical data format, which may be a simple reordering or change in the use of whitespace that doesn't change the value of the object but changes the sequence of bytes.

It's important to note that (except for CSV) these representations are biased towards representing a single Python object. While that single object can be the list of objects, it's still list of a fixed size. In order to process one of the objects, the entire list must be de-serialized. There are...

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