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RIS citation export for THPDP061: Python Expert Applications for Large Beam Instrumentation Systems at CERN

TY  - CONF
AU  - Martínez Samblas, J.
AU  - Calvo Giraldo, E.
AU  - Gonzalez-Berges, M.
AU  - Krupa, M.
ED  - Schaa, Volker RW
ED  - Götz, Andy
ED  - Venter, Johan
ED  - White, Karen
ED  - Robichon, Marie
ED  - Rowland, Vivienne
TI  - Python Expert Applications for Large Beam Instrumentation Systems at CERN
J2  - Proc. of ICALEPCS2023, Cape Town, South Africa, 09-13 October 2023
CY  - Cape Town, South Africa
T2  - International Conference on Accelerator and Large Experimental Physics Control Systems
T3  - 19
LA  - english
AB  - 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. 
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 1460
EP  - 1464
KW  - controls
KW  - operation
KW  - software
KW  - detector
KW  - MMI
DA  - 2024/02
PY  - 2024
SN  - 2226-0358
SN  - 978-3-95450-238-7
DO  - doi:10.18429/JACoW-ICALEPCS2023-THPDP061
UR  - https://jacow.org/icalepcs2023/papers/thpdp061.pdf
ER  -