Tools and Environments
Parts 1 to 3: The In-Browser Sandbox
The first three parts of the course run entirely in the course’s in-browser sandbox. You do not need to install anything to start the course.
The sandbox provides:
- a code area where you write Python,
- an output area where you see what the program prints,
- and an input area where the program can ask you for values.
You open the sandbox by clicking the Python icon at the side of the page. The sandbox runs the code locally in your browser, so it is fast and does not depend on a network connection during normal use.
The sandbox is the main place you will write and run code through the first three parts. Most chapter examples are short enough to copy into the sandbox, run, and modify in a few seconds.
Parts 4 and Beyond: A Local Python Install
Starting in Part 4, the course assumes you have Python installed on your own computer. The sandbox keeps working for short experiments, but the project moves to a real local environment because it needs to read and write files.
To work comfortably on the local parts of the course, you will need:
- a recent version of Python (3.10 or later),
- a code editor such as Visual Studio Code or another editor intended for writing code,
- a browser,
- and a terminal where you can run commands such as
python main.py.
Detailed installation instructions for macOS, Windows, and Linux are provided as a separate document at the end of Part 3, together with a short verification script that confirms the install works.
If working with terminals and local development tools feels awkward on Windows, using Windows Subsystem for Linux (WSL) may make the workflow smoother. The exact setup is up to you, but the main goal is to have a predictable environment where Python, the terminal, and the editor work well together.
The examples in these materials have been written and tested in a Linux environment, but they should also work on macOS and on Windows — with or without WSL. If you run into issues, check the documentation of your tools and consider asking for help in the course forums or support channels.
Libraries Used Later in the Course
Later parts introduce a small number of libraries:
- pandas for summarizing tabular data, in Part 7,
- and a plotting library for producing charts, in Part 8.
These are installed using pip, Python’s standard package manager. The exact installation steps are covered when each library is first used. You do not need to install them before the parts that use them.
A Working Folder for the Project
Once you move to a local Python install, the project keeps growing in one folder for the rest of the course. You do not start a new project in each part. Instead, you keep extending the same folder.
The folder structure stays relatively stable. New files appear as the project grows — for example, a function module, a data file, a chart script — but the same folder serves as the home for the project from Part 4 to the end.
If you want a part-by-part overview of how the project grows, keep the Project Roadmap nearby while studying.