arXiv 2410.021122024-10hep-exphysics.comp-ph

PyHEP.dev 2024 研讨会总结报告，2024年8月26日至30日，德国亚琛

PyHEP.dev 2024 Workshop Summary Report, August 26-30 2024, Aachen, Germany

Azzah Alshehri, Jan Bürger, Saransh Chopra, Niclas Eich, Jonas Eppelt, Martin Erdmann, Jonas Eschle, Peter Fackeldey, Maté Farkas, Matthew Feickert, Tristan Fil… 展开作者

Azzah Alshehri, Jan Bürger, Saransh Chopra, Niclas Eich, Jonas Eppelt, Martin Erdmann, Jonas Eschle, Peter Fackeldey, Maté Farkas, Matthew Feickert, Tristan Fillinger, Benjamin Fischer, Stefan Fröse, Lino Oscar Gerlach, Nikolai Hartmann, Alexander Heidelbach, Alexander Held, Marian I Ivanov, Josué Molina, Yaroslav Nikitenko, Ianna Osborne, Vincenzo Eduardo Padulano, Jim Pivarski, Cyrille Praz, Marcel Rieger, Eduardo Rodrigues, Oksana Shadura, Juraj Smieško, Giordon Holtsberg Stark, Judith Steinfeld, Angela Warkentin

备注：: 16 pages, 0 figures; workshop summary

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AI总结：

该报告总结了2024年PyHEP.dev研讨会，聚焦高能物理Python分析工具与趋势，涵盖数据分析范围、统计模型、工作流及分布式处理等关键议题。

摘要：

第二届 PyHEP.dev 研讨会，作为由高能物理软件基金会（HSF）组织的“高能物理开发者中的 Python”系列的一部分，于2024年8月26日至30日在德国亚琛举行。此次会议汇集了近30名 Python 包开发者、维护者和高级用户，就 Python 的当前趋势进行非正式讨论，主要关注高能物理（HEP）中的分析工具和技术。\n 研讨会议程涵盖了一系列主题，例如界定高能物理数据分析的范围、探索分析大挑战项目、评估统计模型和序列化方法、评估工作流管理系统、检查直方图实践，以及调查分布式处理工具如 RDataFrame、Coffea 和 Dask。此外，研讨会还专门安排了时间讨论未来 PyHEP.dev 活动的组织，延续在欧洲和美国之间交替作为主办地点的传统。\n 本文件由会议召集人在研讨会后的数周内编写，总结了出现的关键讨论、突出要点和结论。

英文摘要：

The second PyHEP.dev workshop, part of the "Python in HEP Developers" series organized by the HEP Software Foundation (HSF), took place in Aachen, Germany, from August 26 to 30, 2024. This gathering brought together nearly 30 Python package developers, maintainers, and power users to engage in informal discussions about current trends in Python, with a primary focus on analysis tools and techniques in High Energy Physics (HEP). The workshop agenda encompassed a range of topics, such as defining the scope of HEP data analysis, exploring the Analysis Grand Challenge project, evaluating statistical models and serialization methods, assessing workflow management systems, examining histogramming practices, and investigating distributed processing tools like RDataFrame, Coffea, and Dask. Additionally, the workshop dedicated time to brainstorming the organization of future PyHEP.dev events, upholding the tradition of alternating between Europe and the United States as host locations. This document, prepared by the session conveners in the weeks following the workshop, serves as a summary of the key discussions, salient points, and conclusions that emerged.

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