DeerLab, an open-source Python-based software package, is introduced for analyzing dipolar EPR spectroscopy data. It implements a variety of methods including one-step analysis, multi-pathway models, and global analysis to improve accuracy and reliability in distance distribution determination.

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This paper presents a useful new software tool for EPR data analysis that offers several methodological improvements, including one-step analysis, multi-pathway models, and global analysis with non-parametric distributions. While more validation with real-world data and a stronger focus on uncertainty analysis would be beneficial, the open-source nature of DeerLab allows for flexibility and adaptability, making it a valuable contribution to the field. Thus it receives a rating of 4.