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Python Object-Oriented Programming

You're reading from   Python Object-Oriented Programming Build robust and maintainable object-oriented Python applications and libraries

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781801077262
Length 714 pages
Edition 4th 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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Toc

Table of Contents (17) Chapters Close

Preface 1. Object-Oriented Design 2. Objects in Python FREE CHAPTER 3. When Objects Are Alike 4. Expecting the Unexpected 5. When to Use Object-Oriented Programming 6. Abstract Base Classes and Operator Overloading 7. Python Data Structures 8. The Intersection of Object-Oriented and Functional Programming 9. Strings, Serialization, and File Paths 10. The Iterator Pattern 11. Common Design Patterns 12. Advanced Design Patterns 13. Testing Object-Oriented Programs 14. Concurrency 15. Other Books You May Enjoy
16. Index

Case study

In the previous chapters of the case study, we've been skirting an issue that arises frequently when working with complex data. Files have both a logical layout and a physical format. We've been laboring under a tacit assumption that our files are in CSV format, with a layout defined by the first line of the file. In Chapter 2, we touched on file loading. In Chapter 6, we revisited loading data and partitioning it into training and testing sets.

In both previous chapters, we trusted that the data would be in a CSV format. This isn't a great assumption to make. We need to look at the alternatives and elevate our assumptions into a design choice. We also need to build in the flexibility to make changes as the context for using our application evolves.

It's common to map complex objects to dictionaries, which have a tidy JSON representation. For this reason, the Classifier web application makes use of dictionaries. We can also parse CSV data...

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