Book Image

Scientific Computing with Python 3

By : Claus Führer, Jan Erik Solem, Olivier Verdier
Book Image

Scientific Computing with Python 3

By: Claus Führer, Jan Erik Solem, Olivier Verdier

Overview of this book

Python can be used for more than just general-purpose programming. It is a free, open source language and environment that has tremendous potential for use within the domain of scientific computing. This book presents Python in tight connection with mathematical applications and demonstrates how to use various concepts in Python for computing purposes, including examples with the latest version of Python 3. Python is an effective tool to use when coupling scientific computing and mathematics and this book will teach you how to use it for linear algebra, arrays, plotting, iterating, functions, polynomials, and much more.
Table of Contents (23 chapters)
Scientific Computing with Python 3
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Acknowledgement
Preface
References

Debugging


Debugging is sometimes necessary while testing, in particular if it is not immediately clear why a given test does not pass. In that case, it is useful to be able to debug a given test in an interactive session. This is however, made difficult by the design of the unittest.TestCase class, which prevents easy instantiation of test case objects. The solution is to create a special instance for debugging purpose only.

Suppose that, in the example of the TestIdentity class above, we want to test the test_functionality method. This would be achieved as follows:

test_case = TestIdentity(methodName='test_functionality')

Now this test can be run individually by:

test_case.debug()

This will run this individual test and it allows for debugging.