Treffer: Styx: A multi-language API Generator for Command-Line Tools.

Title:
Styx: A multi-language API Generator for Command-Line Tools.
Authors:
Rupprecht F; Center for Data Analytics, Innovation, and Rigor, Child Mind Institute, 215 East 50th Street, 10022, New York, USA., Kai J; Center for Data Analytics, Innovation, and Rigor, Child Mind Institute, 215 East 50th Street, 10022, New York, USA., Shrestha B; Center for Data Analytics, Innovation, and Rigor, Child Mind Institute, 215 East 50th Street, 10022, New York, USA., Giavasis S; Center for Data Analytics, Innovation, and Rigor, Child Mind Institute, 215 East 50th Street, 10022, New York, USA., Xu T; Center for Data Analytics, Innovation, and Rigor, Child Mind Institute, 215 East 50th Street, 10022, New York, USA., Glatard T; Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, 250 College Street, M5T 1R8, Toronto, Canada., Milham MP; Center for Data Analytics, Innovation, and Rigor, Child Mind Institute, 215 East 50th Street, 10022, New York, USA., Kiar G; Center for Data Analytics, Innovation, and Rigor, Child Mind Institute, 215 East 50th Street, 10022, New York, USA.
Source:
BioRxiv : the preprint server for biology [bioRxiv] 2025 Jul 30. Date of Electronic Publication: 2025 Jul 30.
Publication Type:
Journal Article; Preprint
Language:
English
Journal Info:
Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE
Grant Information:
RF1 MH130859 United States MH NIMH NIH HHS
Contributed Indexing:
Keywords: API; Python; R; TypeScript; code generation; command-line interfaces; informatics; pipelines
Entry Date(s):
Date Created: 20250806 Latest Revision: 20250811
Update Code:
20250811
PubMed Central ID:
PMC12324196
DOI:
10.1101/2025.07.24.666435
PMID:
40766634
Database:
MEDLINE

Weitere Informationen

In numerous scientific domains, established tools have often been developed with complex command-line interfaces. Such is the case for brain imaging and bioinformatics, making the use of powerful legacy tools in modern workflow paradigms challenging. We present (i) Styx, a compiler for generating language-native wrapper functions from static tool metadata, leading to seamless integration of command-line tools within the data science ecosystem. Alongside Styx, we have created (ii) NiWrap, a collection of more than 1900 neuroimaging command-line function descriptions as a proof-of-concept implementation. These interfaces, available in Python, R, and TypeScript (available at https://github.com/styx-api), significantly reduce the complexity of writing and interpreting software pipelines, particularly when composing workflows across packages with distinct API standards. The compiler architecture of Styx facilitates maintainability and portability across computing environments. As with all metadata-dependent infrastructure, creating sufficient metadata annotations remains a barrier to adoption. Accordingly, NiWrap demonstrates approaches that lower this barrier through direct source code extraction and LLM-assisted documentation parsing. Together, Styx and NiWrap offer a sustainable solution for interfacing diverse command-line tools with modern data science ecosystems. This modular approach enhances reproducibility and efficiency in pipeline development while ensuring portability across computing environments and programming languages.

Competing interests No competing interest is declared.