Drew Oldag, Melissa DeLucchi, Wilson Beebe, Doug Branton, Sandro Campos, Colin Orion Chandler, Carl Christofferson, Andrew Connolly, Jeremy Kubica, Olivia Lynn, Konstantin Malanchev, Alex I. Malz, Rachel Mandelbaum, Sean McGuire and Chris Wenneman
{"title":"A Python Project Template for Healthy Scientific Software","authors":"Drew Oldag, Melissa DeLucchi, Wilson Beebe, Doug Branton, Sandro Campos, Colin Orion Chandler, Carl Christofferson, Andrew Connolly, Jeremy Kubica, Olivia Lynn, Konstantin Malanchev, Alex I. Malz, Rachel Mandelbaum, Sean McGuire and Chris Wenneman","doi":"10.3847/2515-5172/ad4da1","DOIUrl":null,"url":null,"abstract":"The creation of “healthy” scientific software is vital for its successful long-term adoption in scientific research. Here healthy code is defined to mean software that is usable, maintainable, and proffers consistently reproducible results. Incorporating tooling and practices to achieve these goals often leads to short-term, yet significant, overhead for new projects. We introduce the LINCC Frameworks Python Project Template, a configurable code template designed for scientific software projects that greatly simplifies adopting best practices by automating the setup and configuration of important tools locally and via a suite of GitHub workflows. Notably, the template does not include any application-specific code, thereby enabling users to focus on their scientific code rather than building or maintaining code infrastructure.","PeriodicalId":74684,"journal":{"name":"Research notes of the AAS","volume":"32 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research notes of the AAS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3847/2515-5172/ad4da1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The creation of “healthy” scientific software is vital for its successful long-term adoption in scientific research. Here healthy code is defined to mean software that is usable, maintainable, and proffers consistently reproducible results. Incorporating tooling and practices to achieve these goals often leads to short-term, yet significant, overhead for new projects. We introduce the LINCC Frameworks Python Project Template, a configurable code template designed for scientific software projects that greatly simplifies adopting best practices by automating the setup and configuration of important tools locally and via a suite of GitHub workflows. Notably, the template does not include any application-specific code, thereby enabling users to focus on their scientific code rather than building or maintaining code infrastructure.
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