斯蒂克斯:一个多语言的API生成器,用于命令行工具.
Florian Rupprecht1, Jason Kai1, Biraj Shrestha1
1Center for Data Analytics, Innovation, and Rigor, Child Mind Institute, 215 East 50th Street, 10022, New York, USA.
bioRxiv : the preprint server for biology
|August 6, 2025
概括
斯泰克斯和NiWrap简化了复杂的命令行工具,用于现代数据科学. 这些工具可以无地集成旧软件,提高科学工作流程的可复制性和效率.
科学领域:
- 生物信息学是一种生物信息学.
- 神经成像是一种神经成像.
- 数据科学数据科学数据科学
背景情况:
- 许多科学领域依赖于传统的命令行工具.
- 复杂的接口阻碍了集成到现代数据科学工作流程,特别是在脑成像和生物信息学.
- 弥合这一差距对于高效和可重复的研究至关重要.
研究的目的:
- 介绍Styx,一个编译器,用于从静态工具元数据生成语言原生封装函数.
- 现在的NiWrap是一系列超过1900个神经成像命令行函数描述的集合.
- 促进命令行工具的无集成到数据科学生态系统中.
主要方法:
- 斯蒂克斯编译器从工具元数据中生成封装函数.
- NiWrap提供了一套全面的神经成像工具描述.
- 接口可以使用Python,R和TypeScript.
- 通过源代码提取和LLM辅助解析来解决元数据注释障碍.
主要成果:
- 斯泰克斯和NiWrap显著降低了编写和解释软件管道的复杂性.
- 能够在不同API标准的包中构建工作流程.
- 展示了降低元数据注释障碍的方法.
结论:
- 斯泰克斯和NiWrap提供了一个可持续的解决方案,用于将各种命令行工具与现代数据科学连接起来.
- 在计算环境和编程语言中提高可重现性,效率和可移植性.
- 促进在当代研究范式中使用强大的遗留工具.
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