py2many: Universal Python Transpiler to Rust, C++, Go, and More

Introduction

py2many is a robust Python transpiler that transforms Python source code into various statically-typed programming languages. It supports conversion to Rust, C++, Go, Zig, Julia, Nim, Dart, V, and D, with a primary focus on Python to Rust and production-ready support for C++. This tool enables developers to dramatically improve execution speed, enhance security by moving to safer systems languages, and facilitate cross-platform development.

Key features include multi-language support, automatic type inference, generation of optimized code for systems programming languages, and cross-platform compatibility across Linux, macOS, and Windows. py2many also serves as an excellent educational tool for learning new languages by comparing Python implementations with their transpiled equivalents.

Installation

To get started with py2many, you'll need Python 3.8+ installed.

Install via pip:

pip3 install --user py2many # installs to $HOME/.local

OR

sudo pip3 install py2many # installs systemwide

Examples

See how py2many converts Python code to idiomatic Rust:

Original Python code:

def fib(i: int) -> int:
    if i == 0 or i == 1:
        return 1
    return fib(i - 1) + fib(i - 2)

# Demonstrate overflow handling
def add(i: i32, j: i32):
    return i + j

Transpiled Rust code:

fn fib(i: i32) -> i32 {
    if i == 0 || i == 1 {
        return 1;
    }
    return (fib((i - 1)) + fib((i - 2)));
}

// return type is i64
pub fn add(i: i32, j: i32) -> i64 {
    return ((i as i64) + (j as i64)) as i64;
}

To transpile your Python code to different languages, use the py2many command with the desired target language flag:

# Python to Rust
py2many --rust tests/cases/fib.py

# Python to C++
py2many --cpp tests/cases/fib.py

# Python to Go
py2many --go tests/cases/fib.py

You can find more transpiled examples for all supported languages in the official repository's tests/expected directory: More Examples.

Why Use py2many

py2many offers several compelling reasons for its adoption:

• Performance: Dramatically improve execution speed by transpiling Python to languages like Rust, C++, or Go, while retaining Python's development ease.
• Security: Write security-sensitive code in Python, verify it, then transpile to safer systems languages like Rust to mitigate common vulnerabilities.
• Cross-platform Development: Accelerate Python code by converting it into native extensions or standalone applications for various platforms.
• Mobile & Systems Programming: Develop once in Python and deploy to multiple targets, offering an alternative to platform-specific solutions.
• Learning Tool: An excellent resource for learning new programming languages by comparing Python implementations with their transpiled counterparts.

Links

For more information, examples, and to contribute to the project, please visit the official resources:

• py2many GitHub Repository
• View Transpiled Examples
• Contributing Guidelines