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Title Python Expert Applications for Large Beam Instrumentation Systems at CERN
  • J. Martínez Samblas, E. Calvo Giraldo, M. Gonzalez-Berges, M. Krupa
    CERN, Meyrin, Switzerland
Abstract In recent years, beam diagnostics systems with increasingly large numbers of monitors, and systems handling vast amounts of data have been deployed at CERN. Their regular operation and maintenance poses a significant challenge. These systems have to run 24/7 when the accelerators are operating and the quality of the data they produce has to be guaranteed. This paper presents our experience developing applications in Python which are used to assure the readiness and availability of these large systems. The paper will first give a brief introduction to the different functionalities required, before presenting the chosen architectural design. Although the applications work mostly with online data, logged data is also used in some cases. For the implementation, standard Python libraries (e.g. PyQt, pandas, NumPy) have been used, and given the demanding performance requirements of these applications, several optimisations have had to be introduced. Feedback from users, collected during the first year’s run after CERN’s Long Shutdown period and the 2023 LHC commissioning, will also be presented. Finally, several ideas for future work will be described.
Paper download THPDP061.PDF [1.768 MB / 5 pages]
Poster download THPDP061_POSTER.PDF [2.005 MB]
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Conference ICALEPCS2023
Series International Conference on Accelerator and Large Experimental Physics Control Systems (19th)
Location Cape Town, South Africa
Date 09-13 October 2023
Publisher JACoW Publishing, Geneva, Switzerland
Editorial Board Volker RW Schaa (GSI, Darmstadt, Germany); Andy Götz (ESRF, Grenoble, France); Johan Venter (SARAO, Cape Town, South Africa); Karen White (SNS, Oak Ridge, TN, USA); Marie Robichon (ESRF, Grenoble, France); Vivienne Rowland (SARAO, Cape Town, South Africa)
Online ISBN 978-3-95450-238-7
Online ISSN 2226-0358
Received 05 October 2023
Revised 26 October 2023
Accepted 13 December 2023
Issued/td> 21 December 2023
DOI doi:10.18429/JACoW-ICALEPCS2023-THPDP061
Pages 1460-1464
Creative Commons CC logoPublished by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 International license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI.