2026-07-22T06:31:11Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:16752 2024-03-06T10:31:48Z ddc:004 open_access

Extending PyJL - Transpiling Python Libraries to Julia Marcelino, Miguel Leitão, António Menezes Source-to-Source Compiler Automatic Transpilation Library Translation Python 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Miguel Marcelino and António Menezes Leitão 2022 Is Part Of OASIcs, Volume 104, 11th Symposium on Languages, Applications and Technologies (SLATE 2022) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.SLATE.2022.6 urn:nbn:de:0030-drops-167525 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2022.6 eng https://creativecommons.org/licenses/by/4.0/legalcode