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Learning Jupyter 5

You're reading from   Learning Jupyter 5 Explore interactive computing using Python, Java, JavaScript, R, Julia, and JupyterLab

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Product type Paperback
Published in Aug 2018
Publisher
ISBN-13 9781789137408
Length 282 pages
Edition 2nd Edition
Languages
Tools
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Toc

Table of Contents (18) Chapters Close

Title Page
Packt Upsell
Contributors
Preface
1. Introduction to Jupyter FREE CHAPTER 2. Jupyter Python Scripting 3. Jupyter R Scripting 4. Jupyter Julia Scripting 5. Jupyter Java Coding 6. Jupyter JavaScript Coding 7. Jupyter Scala 8. Jupyter and Big Data 9. Interactive Widgets 10. Sharing and Converting Jupyter Notebooks 11. Multiuser Jupyter Notebooks 12. What's Next? 1. Other Books You May Enjoy Index

Julia unit testing


As a full language, Julia has unit-testing abilities to make sure that your code is performing as expected. The unit tests usually reside in the tests folder.

Two of the standard functions available for unit testing in Julia are FactCheck and Base.Test. They both do the same thing, but react differently to failed tests. FactCheck will generate an error message that will not stop processing on a failure. If you provide an error handler, that error handler will take control of the test.

Base.Test will throw an exception and stop processing on the first test failure. In that regard, it is probably not useful as a unit-testing function so much as a runtime test that you may put in place to make sure parameters are within reason or otherwise. Just stop processing before something bad happens.

 

Both packages are built in to the standard Julia distributions.

As an example, we can create a unit tests Notebook that does the same tests and see the resulting, different responses for...

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