Computer Science from Scratch: Building Interpreters, Art, Emulators, and ML in Python

Knowing Python syntax is one thing; understanding what happens beneath it is another. Computer Science from Scratch uses substantial, code-centered projects to make foundational ideas tangible—from how interpreters parse and run programs to how emulators reproduce the behavior of older machines.

David Kopec’s book is written for readers who already program in Python and want to see more of the machinery behind computing. Instead of treating computer science as a collection of abstractions, it invites readers to build working examples and learn from the decisions those implementations require.

Explore computing by building it

The projects range across several distinctive areas: programming-language interpreters, algorithmic art and computer graphics, CHIP-8 and NES emulators, and introductory machine learning. That variety gives readers a chance to connect software concepts with visual output, virtual machines, and data-driven predictions.

From parsing to machine learning

• Interpreters: Explore how a programming language is represented, parsed, and executed by implementing small interpreters.
• Graphics and art: Use code to investigate image manipulation and algorithmic approaches to visual work.
• Emulators: Study computer architecture and instruction handling through virtual-machine and console-emulation projects.
• Machine learning: Work through k-nearest-neighbors classification and regression to see how a simple learning method can make predictions.

A project-led route into computer science

Each project offers a concrete way to examine an underlying concept: the code is not just an end product, but a lens for understanding how computing works. The book also provides context, exercises, and extensions for readers who want to think beyond the initial implementation. An appendix reviews bitwise operations, useful when working close to the level of machine instructions.

Who will appreciate this book?

This is best suited to intermediate Python programmers—not complete programming beginners—who are curious about interpreters, computer architecture, emulation, graphics, or the mechanics of basic machine-learning methods. It offers a practical way to connect programming practice with the principles that make software and computers behave as they do.

If you’re ready to move past writing code and start examining how it works, this ebook provides a lively set of projects for doing exactly that.