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You're reading from  Learning Jupyter

Product typeBook
Published inNov 2016
Reading LevelIntermediate
PublisherPackt
ISBN-139781785884870
Edition1st Edition
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Dan Toomey
Dan Toomey
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Dan Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.
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Julia unit testing


As a full language, Julia has unit testing abilities to make sure 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 can 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 errors...

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Learning Jupyter
Published in: Nov 2016Publisher: PacktISBN-13: 9781785884870

Author (1)

author image
Dan Toomey

Dan Toomey has been developing application software for over 20 years. He has worked in a variety of industries and companies, in roles from sole contributor to VP/CTO-level. For the last few years, he has been contracting for companies in the eastern Massachusetts area. Dan has been contracting under Dan Toomey Software Corp. Dan has also written R for Data Science, Jupyter for Data Sciences, and the Jupyter Cookbook, all with Packt.
Read more about Dan Toomey