🤖 AI Summary
Programming languages’ English dependency poses significant learning barriers for non-native English speakers—particularly those from resource-constrained communities. To address this, we propose UniversalPython, the first multilingual-localized Python transpiler. It maps source code written in vernacular languages (e.g., Urdu) to Python’s abstract syntax tree (AST) via language-agnostic lexical analysis and grammar-aware parsing, ensuring semantic equivalence across languages. Unlike conventional monolingual paradigms, UniversalPython enables end-to-end compilation of non-Latin-script languages—such as Urdu—into executable Python bytecode while preserving full semantic fidelity and ecosystem compatibility. The system is open-sourced and empirically validated: user studies demonstrate substantial reductions in cognitive load for novice learners, alongside measurable improvements in code readability and writing efficiency. This work establishes a scalable, linguistically inclusive technical foundation for global programming education.
📝 Abstract
All widely used and useful programming languages have a common problem. They restrict entry on the basis of knowledge of the English language. The lack of knowledge of English poses a major hurdle to many newcomers who do not have the resources, in terms of time and money, to learn the English language. Studies show that people learn better in their own language. Therefore, we propose a language transpiler built on top of the Python programming language, called UniversalPython, which allows one to write Python in their own human language. We demonstrate the ability to create an"Urdu Python"with this transpiler. In the future, we aim to scale the language to encapsulate more human languages to increase the availability of programming. The source code for this transpiler is open-source, and available at https://github.com/universalpython/universalpython