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Modern Python Cookbook

You're reading from   Modern Python Cookbook 133 recipes to develop flawless and expressive programs in Python 3.8

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781800207455
Length 822 pages
Edition 2nd 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 (18) Chapters Close

Preface 1. Numbers, Strings, and Tuples 2. Statements and Syntax FREE CHAPTER 3. Function Definitions 4. Built-In Data Structures Part 1: Lists and Sets 5. Built-In Data Structures Part 2: Dictionaries 6. User Inputs and Outputs 7. Basics of Classes and Objects 8. More Advanced Class Design 9. Functional Programming Features 10. Input/Output, Physical Format, and Logical Layout 11. Testing 12. Web Services 13. Application Integration: Configuration 14. Application Integration: Combination 15. Statistical Programming and Linear Regression 16. Other Books You May Enjoy
17. Index

Testing things that involve randomness

Many applications rely on the random module to create random values or put values into a random order. In many statistical tests, repeated random shuffling or random selection is done. When we want to test one of these algorithms, any intermediate results or details of the processing are essentially impossible to predict.

We have two choices for trying to make the random module predictable enough to write meaningful unit tests:

  • Set a known seed value; this is common, and we've made heavy use of this in many other recipes
  • Use unittest.mock to replace the random module with something predictable

In this recipe, we'll look at ways to unit test algorithms that involve randomness.

Getting ready

Given a sample dataset, we can compute a statistical measure such as a mean or median. A common next step is to determine the likely values of these statistical measures for some overall population....

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