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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
Who this book is for
What this book covers
To get the most out of this book
Get in touch
1. Preliminaries, Tools, and Techniques FREE CHAPTER 2. The __init__() Method 3. Integrating Seamlessly - Basic Special Methods 4. Attribute Access, Properties, and Descriptors 5. The ABCs of Consistent Design 6. Using Callables and Contexts 7. Creating Containers and Collections 8. Creating Numbers 9. Decorators and Mixins - Cross-Cutting Aspects 10. Serializing and Saving - JSON, YAML, Pickle, CSV, and XML 11. Storing and Retrieving Objects via Shelve 12. Storing and Retrieving Objects via SQLite 13. Transmitting and Sharing Objects 14. Configuration Files and Persistence 15. Design Principles and Patterns 16. The Logging and Warning Modules 17. Designing for Testability 18. Coping with the Command Line 19. Module and Package Design 20. Quality and Documentation

Documentation – sphinx and RST markup

All Python code should have docstrings at the module, class and method level. Not every single method requires a docstring. Some method names are really well chosen, and little more needs to be said. Most times, however, documentation is essential for clarity.

Python documentation is often written using the reStructuredText (RST) markup.

Throughout the code examples in the book, however, we'll omit docstrings. The omission keeps the book to a reasonable size. This gap has the disadvantage of making docstrings seem optional. They're emphatically not optional.

This point is so important, we'll emphasize it again: docstrings are essential.

The docstring material is used three ways by Python:

  • The internal help() function displays the docstrings.
  • The doctest tool can find examples in docstrings and run them as test cases.
  • External tools, such as sphinx and pydoc, can produce elegant documentation extracts from these strings.

Because of the relative simplicity of RST, it's quite easy to write good docstrings. We'll look at documentation and the expected markup in detail in Chapter 18, Coping with the Command Line. For now, however, we'll provide a quick example of what a docstring might look like:

def factorial(n: int) -> int:
"""
Compute n! recursively.

:param n: an integer >= 0
:returns: n!

Because of Python's stack limitation, this won't
compute a value larger than about 1000!.

>>> factorial(5)
120
"""
if n == 0:
return 1
return n*factorial(n-1)

This shows the RST markup for the n parameter and the return value. It includes an additional note about limitations. It also includes a doctest example that can be used to validate the implementation using the doctest tool. The use of :param n: and :return: identifies text that will be used by the sphinx tool to provide proper formatting and indexing of the information.

You have been reading a chapter from
Mastering Object-Oriented Python - Second Edition
Published in: Jun 2019
Publisher: Packt
ISBN-13: 9781789531367
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