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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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Toc

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

Writing unit tests with doctest

It is a widely adopted practice to provide concrete examples of classes and functions in docstrings. As shown in the preceding example, we can provide the following kind of example text in a docstring:

>>> p_1 = Point(22, 7)
>>> p_2 = Point(20, 5)
>>> round(p_1.dist(p_2),4)
2.8284

A concrete example has many benefits. The goal of Python code is to be beautiful and readable. If the code sample is obscure or confusing, this is a design problem that really should be resolved. Writing more words in comments to try to explain bad code is a symptom of a deeper problem. A concrete example should be as clear and expressive as the code itself.

An additional benefit of concrete examples is that they are test cases. The doctest module can scan each docstring to locate these examples, build, and execute test cases. This will confirm that the output in the example matches the actual output.

One common approach to using doctest is to include the...

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