{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pyexperimenter-easily-distribute-experiments","title":"PyExperimenter: Easily distribute experiments and track results","arxiv_id":"2301.06348","date":"2023-01-16","proceeding":null,"authors":["Tanja Tornede","Alexander Tornede","Lukas Fehring","Lukas Gehring","Helena Graf","Jonas Hanselle","Felix Mohr","Marcel Wever"],"abstract":"PyExperimenter is a tool to facilitate the setup, documentation, execution, and subsequent evaluation of results from an empirical study of algorithms and in particular is designed to reduce the involved manual effort significantly. It is intended to be used by researchers in the field of artificial intelligence, but is not limited to those.","url_abs":"https://arxiv.org/abs/2301.06348v2","url_pdf":"https://arxiv.org/pdf/2301.06348v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"pyexperimenter-easily-distribute-experiments","repo_url":"https://github.com/tornede/py_experimenter","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}