A note on skills required
These projects demand a wide variety of skills, including software and data architecture, design, Python programming, test design, and even documentation writing. This breadth of skills reflects the author’s experience in enterprise software development. Developers are expected to be generalists, able to follow technology changes and adapt to new technology.
In some of the earlier chapters, we’ll offer some guidance on software design and construction. The guidance will assume a working knowledge of Python. It will point you toward the documentation for various Python packages for more information.
We’ll also offer some details on how best to construct unit tests and acceptance tests. These topics can be challenging because testing is often under-emphasized. Developers fresh out of school often lament that modern computer science education doesn’t seem to cover testing and test design very thoroughly.
This book will emphasize using pytest for unit tests and behave for acceptance tests. Using behave means writing test scenarios in the Gherkin language. This is the language used by the cucumber tool and sometimes the language is also called Cucumber. This may be new, and we’ll emphasize this with more detailed examples, particularly in the first five chapters.
Some of the projects will implement statistical algorithms. We’ll use notation like x to represent the mean of the variable x. For more information on basic statistics for data analytics, see Statistics for Data Science:
https://www.packtpub.com/product/statistics-for-data-science/9781788290678
