Abstract

Thanks to the recent multiplication of scientific Python packages in the open-source software landscape, Data Acquisition frameworks (DAQ-Fs) appear as versatile replacements of custom-made or costly commercial solutions. PyMoDAQ is a DAQ-F focusing on easy-to-use graphical user interfaces allowing a simple control and automation of a large variety of experimental setups. Its development included a highly modular structure allowing any experimental data acquisition as a function of multiple varying parameters. It offers numerous additional functionalities: instrument and setup configuration, plotting, saving, logging, etc. Live visual feedback is available at all times to monitor the ongoing experiment. Flexibility of its user interfaces is the key advantage of PyMoDAQ allowing also its integration as the core of more focused applications. Its hierarchical binary format data saving mechanism includes experimental metadata highly compatible with FAIR (Findable, Accessible,Interoperable, Reusable) data. Among the presented characteristics, seven criteria have been chosen to judge the pertinence of PyMoDAQ as a versatile DAQ-F. They are also the basis for a comparison with other existing frameworks highlighting the novelty of PyMoDAQ.

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