Preface
The use of Python is increasing not only in software development, but also in fields such as data science, machine learning, data analysis, research science, finance, and just about all other industries. The growth of Python in many critical fields also comes with the desire to properly, effectively, and efficiently put software tests in place to make sure the programs run correctly and produce the correct results. In addition, more and more software projects are embracing continuous integration and including an automated testing phase. There is still a place for exploratory manual testing—but thorough manual testing of increasingly complex projects is infeasible. Teams need to be able to trust the tests being run by the continuous integration ...
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