Abstract: While we don’t always think about it this way, the job or the data scientist is to build software. Often data scientists use only the most rudimentary of software engineering tools. It’s time we leverage the tools and best practices of software engineering that have been built over the last 25 years. This workshop covers the less sexy, but critical parts of building software: project structure, testing, debugging (the world beyond print statements), logging, source control, linting, and collaboration. The workshop will cover these topics in a hands on way looking at Python code through the IDE, Jupyter notebooks, and at the command line. The workshop will be useful to anyone who does data science in Python and wants to build more robust and reliable code.