Jupyter Notebooks are a popular and powerful tool used in data science that allow you to create and share documents that blend descriptive content with executable code. This blending of code and content can also be a powerful tool for empowering testers through automation.
Introducing Jupyter notebooks into your test automation strategy allows you to harness test automation code and extend its uses to benefit the day to day activities of testers, supporting quality and reducing the pain of repetitive or time consuming tasks.
In this session I’ll provide an introduction to Jupyter Notebooks and the variety of programming languages that they support. Then I will discuss and demonstrate some of the practical use cases of how the notebooks can be used with selenium, api clients and even existing automation page models to create: