Treffer: Extending PyJL - Transpiling Python Libraries to Julia

Many high-level programming languages have emerged in recent years. Julia is one of these languages, claiming to offer the speed of C, the macro capabilities of Lisp, and the user-friendliness of Python. Julia’s syntax is one of its major strengths, making it ideal for scientific and numerical computing. Furthermore, Julia’s high-performance on modern hardware makes it an appealing alternative to Python. However, Python has a considerable advantage over Julia: its extensive library set. There have been efforts to make Python libraries available to Julia either through Foreign Function Interfaces (FFI’s), or through manual translation, but both have their tradeoffs: FFI’s do not take advantage of Julia’s performance, as they call Python’s Virtual Machine, and manual translation is demanding and time-consuming. To address these issues and bridge the gap between the two languages, we propose PyJL, a transpilation tool that converts Python source-code to human-readable Julia source-code. Although the development of PyJL is still at an early stage, our preliminary results reveal that the generated code follows the pragmatics of Julia and is capable of high performance.