In the last chapter, we worked through examples of how we can use Python and the SciPy libraries as a graphical scientific calculator. When we are solving problems one-off, this is fine. However, STEM researchers are often confronted with problems that they must solve over and over. Within the subject that is a focus of this book, that includes working with the same kind of datasets generated during the run of an experiment. In this case, we can vastly improve our efficiency and accuracy by automating tasks through programming. This is a long chapter that takes several class days to cover. But once we get through it, students have been acquainted with what it takes to make code production-ready.