{"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/dragons-a-quick-overview","title":"DRAGONS -- A Quick Overview","arxiv_id":"2310.03048","date":"2023-10-03","proceeding":null,"authors":["Kathleen Labrie","Chris Simpson","Ricardo Cardenes","James Turner","Monika Soraisam","Bruno Quint","Oliver Oberdorf","Vinicius M. Placco","Daniel Berke","Olesja Smirnova","Simon Conseil","William D. Vacca","Joanna Thomas-Osip"],"abstract":"DRAGONS (Data Reduction for Astronomy from Gemini Observatory North and South) is a platform for the reduction and processing of astronomical data. The Python-based, open-source package includes infrastructure for automation and algorithms for the processing of imaging and spectroscopic data, up to the analysis-ready stage. DRAGONS currently focuses on the reduction of Gemini data, although it allows for support of data from other instruments and telescopes through third-party extensions. Its latest release (v3.1) enables automated reduction of all currently-active Gemini imaging facility instruments, as well as optical longslit spectroscopic data, acquired with GMOS.","url_abs":"https://arxiv.org/abs/2310.03048v1","url_pdf":"https://arxiv.org/pdf/2310.03048v1.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":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"dragons-a-quick-overview","repo_url":"https://github.com/geminidrsoftware/dragons","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}