The book assumes you have created a folder called Learning which contains most of the Jupyter Notebooks as we well as assorted *.py files used in the book. A few additional subfolders exist within Learning, namely swimdata, swimdata2, webapp, and charts. If you follow along with the book, you'll end up creating the same (or a very similar) folder structure to this one.

Unlike the folder structure used in the book, this repository is organised by chapter to make it easier to find each chapter's files/resources. To ensure the notebooks in the individual chapter folders work, some of the subfolders, source files, and notebooks from Learning might be repeated (e.g., swimdata, swimclub.py, and so on). This shouldn't really be a problem, especially if you are following along with the book and create the required folder structure as you go. (Hint, hint).

The Everything.zip file contains a compressed archive containing all of the folders/code shown above (should you want a straightforward single-file download option).

There are a number of SQLite plugins for VS Code which allow you to view/manipulate your SQLite database files (independently of Python or Jupyter Notebook). That said, we really like Simon Willison's Datasette tool, which you can pip install from PyPI. Learn more here.

Please take a look at the CodeIndex.pdf file which includes some supplemental code indexing information.