The `faif/python-patterns` repository is a curated collection of Gang of Four (GoF) and other classic software design patterns, implemented in idiomatic Python. Each pattern is contained in a single, self-contained module under organized directories (creational, structural, behavioral, fundamental, other). The code is the ground truth: every module includes a `main()` function that runs doctests demonstrating usage, alongside dedicated unit tests in a parallel `tests/` directory. The implementations are not boilerplate; many demonstrate advanced Python features such as descriptors (strategy.py), metaclasses (registry.py), weak references (flyweight.py), context managers (pool.py), and closures (memento.py). The repo serves as a reference for learning or adopting design patterns in Python, with clear docstrings and examples from the Python ecosystem where applicable. It has no external runtime dependencies, relying solely on the Python standard library, making it universally applicable for study or light reuse.
This repository is the source code and build toolchain for the Go by Example website (https://gobyexample.com), an educational tutorial for the Go programming language (a concurrent, channel-based language). The site teaches Go through annotated example programs. The repository contains example source files (Go code with embedded documentation), a set of command-line tools written in Go that parse these examples, render them into HTML using templates, and output a static site. The build pipeline includes syntax highlighting via chroma, Markdown rendering via blackfriday, and deployment to S3. The project also includes a local preview server, a line length enforcer, and CI/CD via GitHub Actions that regenerates the site and diffs against the committed output to ensure consistency. The architecture is a collection of focused Go tools (generate, serve, upload, measure, test) orchestrated by shell scripts. The codebase demonstrates clean separation of concerns, template-driven HTML generation, and a custom lexer for shell output formatting.
This repository is a comprehensive Python tutorial (28k+ stars) covering beginner to advanced topics, with content written in Markdown and published as a static documentation site via MkDocs. The codebase includes a custom tool (`tools/example_runner.py`) that extracts and executes Python code blocks from the Markdown files to verify correctness, integrated into CI. The project also uses modern Python tooling (uv, ruff, pytest) and provides an interactive learning site at learn-py.org. While primarily educational content, the repository demonstrates solid engineering practices with automated testing of examples, dependency management, and CI/CD pipelines.
This repository is a Chinese translation of the '500 Lines or Less' book (aosabook/500lines), containing twelve educational chapters each implementing a small, self-contained software system in roughly 500 lines of code. The chapters cover diverse topics including a dynamic build system (Contingent), a flow shop scheduler, optical character recognition, static analysis in Julia, an in-memory graph database (Dagoba), a key-value store (DBDB), a 3D modeller, an archaeology-inspired database, a web crawler with async coroutines, a distributed consensus system, a continuous integration system, and a simple web server. The code is intentionally simplified for teaching purposes and is accompanied by Chinese language articles. The repository is a collection of independent applications rather than a single coherent system, and while the code demonstrates clear patterns and architecture, it is largely educational and not production-ready. Many components rely on outdated language versions (Julia 0.3, Python 2.7, JavaScript ES5) and have minimal error handling, making extraction and reuse challenging without modernisation.
This repository is a curated collection of Java interview questions and answers, organized by topics such as Core Java, Collections, Concurrency, Spring, Hibernate, SQL, and more. It also includes several small, self-contained Java projects that demonstrate specific concepts: a custom Stream API implementation (custom-stream), a deadlock example (deadlock), a set of LeetCode algorithm solutions (leetcode-221-maximal-square), and a flawed code review snippet (review). The primary value is the extensive markdown documentation with links to external resources, making it a useful study aid for Java interview preparation. The code examples are educational but not production-grade; the custom-stream project is the most notable for illustrating the internal pipeline pattern of Java Streams. The repository is static and has not been actively updated in some time, though the content remains relevant for many core Java topics.
bioSkills is a curated, archived collection of over 560 bioinformatics 'skills' designed to be consumed by AI coding agents (Claude Code, Codex CLI, etc.). Each skill consists of a SKILL.md containing expert guidance, a usage-guide.md, and one or more self-contained example scripts (Python, R, shell). The repository covers the full breadth of bioinformatics—from sequence manipulation, alignment, and variant calling to single-cell, spatial transcriptomics, and causal genomics. The examples are meticulously commented with version-pinned dependencies and explicit warnings against common pitfalls, reflecting a strong pedagogical focus. The repository is not a live application or library; it is a static knowledge base that has been archived with no further updates planned. Its primary value lies in the expert-compiled recipes and anti-pattern guidance that can steer AI-generated code toward correct methodology.