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Overview

Shed Skin includes over 80 non-trivial example programs totaling more than 25,000 lines of code (measured by sloccount). These examples demonstrate the compiler’s capabilities across a wide range of domains and serve as excellent references for writing Shed Skin-compatible code. The examples range from simple algorithms to complex applications including emulators, game engines, graphics renderers, and computational tools.

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Example Categories

The examples cover diverse application domains:

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Games & Entertainment

  • Chess engines: chess, sunfish
  • Board games: othello, othello2, othello3, score4 (connect four), go
  • Puzzle solvers: sudoku1-5, rubik, rubik2, sokoban, kanoodle, mastermind
  • Classic games: tictactoe, life (Conway’s Game of Life), pylife

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Emulators & Interpreters

  • c64: Full Commodore 64 emulator (3,332 lines)
  • pygasus: NES (Nintendo Entertainment System) emulator (1,510 lines)
  • doom: WAD rendering engine (666 lines)
  • brainfuck: Brainfuck interpreter

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Graphics & Rendering

  • Ray tracers: mao, minilight, pygmy, pylot, yopyra, path_tracing
  • 3D engines: gs (Wolfenstein-like), softrender
  • Fractals: mandelbrot, mandelbrot2, chaos
  • Image processing: hq2x (pixel art scaling), tonyjpegdecoder, minpng, stereo
  • Graphics algorithms: voronoi, voronoi2, pycsg (constructive solid geometry)

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Algorithms & Data Structures

  • Search algorithms: astar (A*), dijkstra, dijkstra2
  • Sorting: timsort
  • Graph algorithms: mwmatching (maximum weighted matching), chull (3D convex hull)
  • Optimization: loop (Havlak loop recognition), genetic, genetic2, adatron (SVM)
  • SAT solvers: sat, pisang

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Compression & Encoding

  • Compression: ac_encode, block (Huffman), lz2 (Lempel-Ziv), tarsalzp, rsync
  • Cryptography: sha (SHA-1), solitaire

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Scientific Computing

  • Physics simulations: nbody, bh (Barnes-Hut), fysphun
  • Machine learning: neural1, neural2, kmeanspp
  • Linear algebra: linalg
  • Quantum computing: quameon (quantum Monte Carlo)

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Benchmarks

  • pystone: Standard Python benchmark
  • richards: Standard benchmark
  • sieve: Prime number sieves (Eratosthenes and Atkin)

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System & Network

  • webserver: Simple web server
  • rdb: iPod shuffle programmer
  • msp_ss: Serial bootstrap loader

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Other

  • plcfrs: Natural language parser
  • collatz: Collatz record sequences
  • ant: TSP (Traveling Salesman Problem) approximation
  • amaze: Maze generator and solver

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Repository

All examples are available in the Shed Skin repository: https://github.com/shedskin/shedskin/tree/master/examples Each example is in its own directory containing:
  • Python source code (.py files)
  • README.md with specific instructions (if needed)
  • Related data files
  • CMakeLists.txt for building

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Running Examples

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Building All Examples

To build and test all examples at once: 
shedskin test
This command will compile and run all examples in the examples directory.

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Building a Single Example

To build and test a specific example: 
shedskin test --target <example_name>
For example, to build the timsort example: 
shedskin test --target timsort

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Manual Compilation

To manually compile and run an example: 
cd examples/mandelbrot
shedskin build mandelbrot
build/mandelbrot

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Extension Modules

Some examples are designed as extension modules (marked with extmod in the examples list). These need to be compiled with the -e flag and imported into Python: 
cd examples/doom
shedskin build -e doom.py
cp build/doom.so .
python doom_main.py

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GUI Examples

Examples marked with GUI require graphics libraries like pygame. Make sure you have the necessary dependencies installed: 
pip install pygame

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Example Complexity

The examples vary significantly in complexity:
  • Simple (< 100 lines): mandelbrot, sieve, life, ant
  • Medium (100-500 lines): chess, dijkstra, neural1, mao, rubik
  • Complex (500-1500 lines): doom, minilight, pygasus, rubik
  • Very Complex (> 1500 lines): c64 (3,332 lines), hq2x, othello3 (22,503 lines with auto-generated code)

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Learning from Examples

When writing code for Shed Skin, these examples serve as excellent references for:
  1. Type patterns: How to structure code so Shed Skin can infer types
  2. Supported features: What Python constructs work with Shed Skin
  3. Performance techniques: How to write fast code
  4. Module usage: How to use the 25+ supported standard library modules
  5. Extension modules: How to create Python-importable modules

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Contributing Examples

If you have an interesting example that works with Shed Skin, please suggest it in the Shedskin discussion group or post an issue in the GitHub repository.