Skip to content

abilian/p2w

Repository files navigation

p2w - Python to WebAssembly Compiler

p2w compiles a substantial subset of Python to WebAssembly, leveraging WASM GC for automatic memory management.

Features

Supported Python Features

  • Data types: integers (arbitrary precision), floats, booleans, strings, bytes, lists, tuples, dicts, sets
  • Control flow: if/elif/else, for/while loops, break/continue, match statements
  • Functions: definitions, default arguments, *args/**kwargs, closures, lambdas, decorators
  • Classes: inheritance, properties, static/class methods, special methods (__init__, __str__, etc.)
  • Comprehensions: list, dict, set, generator expressions
  • Exception handling: try/except/finally, raise, exception chaining
  • Context managers: with statement
  • Generators: yield, generator functions
  • Other: f-strings, type annotations (ignored at runtime), walrus operator, unpacking

JavaScript Interop

p2w provides seamless JavaScript interoperability via the js module:

import js

canvas = js.document.getElementById("chart")
ctx = canvas.getContext("2d")
ctx.fillRect(0, 0, 100, 100)
js.console.log("Hello from Python!")

What Works

Browser Demos

The demos/ directory contains two (somewhat) working browser demos:

  • data-dashboard: Bar chart visualization using Canvas API
  • simulation: Physics simulation with real-time rendering

Golden Programs

The programs/internal/ directory contains 104 test programs covering the supported Python subset. These serve as both regression tests and documentation of working features, including:

  • Classes with inheritance, properties, and special methods
  • Generators and comprehensions
  • Exception handling with chaining
  • Context managers
  • Match statements
  • F-strings and string operations
  • Collection types and methods

Benchmarks

Two benchmark suites validate correctness and measure performance:

programs/benchmarks/ - Classic benchmarks adapted for p2w:

  • fibonacci, primes, sieve, matmul
  • fannkuch, binarytrees, nbody
  • mandelbrot, spectralnorm, fasta
  • pystone

programs/benchmarks-alioth/ - Benchmarks from the Debian Benchmark Game with GCC baseline comparison:

  • binarytrees, nbody, spectralnorm, mandelbrot, fannkuchredux
  • Includes a runner script for automated comparison against GCC (-O3 -ffast-math)

Installation

# Clone the repository
git clone https://git.sr.ht/~sfermigier/p2w
cd p2w

# Install with uv
uv sync

Usage

Command Line

# Compile Python to WAT
uv run p2w source.py > output.wat

# Convert WAT to WASM (requires wabt)
wat2wasm output.wat -o output.wasm

As a Library

from p2w import compile_to_wat

source = """
def fib(n):
    a, b = 0, 1
    for _ in range(n):
        a, b = b, a + b
    return a

print(fib(10))
"""

wat_code = compile_to_wat(source)

Examples

Fibonacci

def fib(n: int) -> int:
    a, b = 0, 1
    for i in range(n):
        a, b = b, a + b
    return a

print(f"fib(30) = {fib(30)}")

Browser Demo

The demos/ directory contains browser examples:

  • data-dashboard: Interactive bar chart visualization
  • simulation: Physics simulation

To run a demo:

cd demos/data-dashboard
make  # Builds app.wasm
# Serve with any HTTP server and open index.html

Development

# Run tests
make test

# Run linting and type checking
make lint

# Format code
make format

# Run tests with coverage
make test-cov

Test Structure

  • tests/a_unit/ - Unit tests
  • tests/b_integration/ - Integration tests
  • tests/c_e2e/ - End-to-end tests

Architecture

p2w follows a straightforward compilation pipeline:

  1. Parse: Python source -> AST (using Python's ast module)
  2. Analyze: Scope analysis, type inference
  3. Compile: AST -> WAT (WebAssembly Text format)
  4. Assemble: WAT -> WASM (via external tools like wat2wasm)

The compiler generates WAT code that uses WASM 3.0 GC features for automatic memory management of Python objects.

Requirements

  • Python 3.12+
  • wabt (for wat2wasm)
  • A WASM runtime with GC support (e.g., recent Chrome/Firefox, wasmtime with GC enabled)

Prior Art and References

It's too long at this point to cite every influence and/or alternative. Here are a few that stand out:

License

MIT

About

Python->WASM compiler

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published