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Python: Real-World Data Science

You're reading from   Python: Real-World Data Science Real-World Data Science

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Product type Course
Published in Jun 2016
Publisher
ISBN-13 9781786465160
Length 1255 pages
Edition 1st Edition
Languages
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Authors (5):
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Fabrizio Romano Fabrizio Romano
Author Profile Icon Fabrizio Romano
Fabrizio Romano
Phuong Vo.T.H Phuong Vo.T.H
Author Profile Icon Phuong Vo.T.H
Phuong Vo.T.H
Robert Layton Robert Layton
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Robert Layton
Sebastian Raschka Sebastian Raschka
Author Profile Icon Sebastian Raschka
Sebastian Raschka
Martin Czygan Martin Czygan
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Martin Czygan
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Table of Contents (12) Chapters Close

Table of Contents FREE CHAPTER
Python: Real-World Data Science
Meet Your Course Guide
What's so cool about Data Science?
Course Structure
Course Journey
The Course Roadmap and Timeline
1. Course Module 1: Python Fundamentals 2. Course Module 2: Data Analysis 3. Course Module 3: Data Mining 4. Course Module 4: Machine Learning Index

Chapter 13. Testing Object-oriented Programs

Skilled Python programmers agree that testing is one of the most important aspects of software development. Even though this chapter is placed near the end of the module, it is not an afterthought; everything we have studied so far will help us when writing tests. We'll be studying:

  • The importance of unit testing and test-driven development
  • The standard unittest module
  • The py.test automated testing suite
  • The mock module
  • Code coverage
  • Cross-platform testing with tox

Why test?

A large collection of programmers already know how important it is to test their code. If you're among them, feel free to skim this section. You'll find the next section—where we actually see how to do the tests in Python—much more scintillating. If you're not convinced of the importance of testing, I promise that your code is broken, you just don't know it. Read on!

Some people argue that testing is more important in Python code because...

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