R-testbench: a Journey in Open Source Programming for Remote Instrumentation with Python

Nowadays, instrumentation involves remote control and test benches automation, because of the required accuracy or to guarantee the safety of the operators. In parallel, open source has known a fast expansion, and has helped scientific communities in industry and research to build strong collaborati...

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Bibliographic Details
Published inSensors & transducers Vol. 245; no. 6; pp. 90 - 98
Main Authors Quenon, Alexandre, Daubie, Evelyne, Moeyaert, Véronique, Dualibe, tunato
Format Journal Article
LanguageEnglish
Published Toronto IFSA Publishing, S.L 01.10.2020
Subjects
Adaptability
Automation
C plus plus
Computer architecture
Control equipment
Feature recognition
instrumentation
Instruments
Libraries
Licensing
Nuclear engineering
Nuclear safety
numpy
Object recognition
Open source software
pandas
Programming languages
python
Remote control
Software
Software development tools
test bench
visa
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Summary:Nowadays, instrumentation involves remote control and test benches automation, because of the required accuracy or to guarantee the safety of the operators. In parallel, open source has known a fast expansion, and has helped scientific communities in industry and research to build strong collaborations to design effective and user-friendly software tools. This paper presents R-testbench, an open source Python library that offers highlevel programming capabilities for instrument remote control and test bench automation. Comparatively to wellknown off-the-shelf software solutions, it has been designed to be open source, reliable, adaptable and userfriendly. It relies on the Virtual Instrumentation Software Architecture (VISA) standard, and enables high-level features, including automatic instrument recognition, thanks to the object-oriented paradigm. It works with PyVISA, a Python front end that calls the VISA libraries, and uses the popular NumPy and pandas packages to offer an optimized data management that is efficient regarding the execution time and the memory use. The proposed library has been validated thanks to continuous integration, performance characterization, and alpha tests in the frame of experiments with nuclear material. It has also been released publicly on the GitHub platform, under the Open Software License 3.0, to be shared with and reviewed by the community.
ISSN:2306-8515
1726-5479