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Mastering Object-Oriented Python

You're reading from   Mastering Object-Oriented Python Build powerful applications with reusable code using OOP design patterns and Python 3.7

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Product type Paperback
Published in Jun 2019
Publisher Packt
ISBN-13 9781789531367
Length 770 pages
Edition 2nd Edition
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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 (25) Chapters Close

Preface 1. Section 1: Tighter Integration Via Special Methods FREE CHAPTER
2. Preliminaries, Tools, and Techniques 3. The __init__() Method 4. Integrating Seamlessly - Basic Special Methods 5. Attribute Access, Properties, and Descriptors 6. The ABCs of Consistent Design 7. Using Callables and Contexts 8. Creating Containers and Collections 9. Creating Numbers 10. Decorators and Mixins - Cross-Cutting Aspects 11. Section 2: Object Serialization and Persistence
12. Serializing and Saving - JSON, YAML, Pickle, CSV, and XML 13. Storing and Retrieving Objects via Shelve 14. Storing and Retrieving Objects via SQLite 15. Transmitting and Sharing Objects 16. Configuration Files and Persistence 17. Section 3: Object-Oriented Testing and Debugging
18. Design Principles and Patterns 19. The Logging and Warning Modules 20. Designing for Testability 21. Coping with the Command Line 22. Module and Package Design 23. Quality and Documentation 24. Other Books You May Enjoy

Specialized logging for control, debugging, audit, and security

There are many kinds of logging; we'll focus on these four varieties:

  • Errors and Control: Basic errors and the control of an application leads to a main log that helps users confirm that the program really is doing what it's supposed to do. This would include enough error information with which users can correct their problems and rerun the application. If a user enables verbose logging, it will amplify this main error and control the log with additional user-friendly details.
  • Debugging: This is used by developers and maintainers; it can include rather complex implementation details. We'll rarely want to enable blanket debugging, but will often enable debugging for specific modules or classes.
  • Audit: This is a formal confirmation that tracks the transformations applied to data so that we can be sure...
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