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However, the dynamic and multimodal nature of mobile eye-tracking data also introduces significant analytical challenges, including the alignment, integration, and interpretation of complex data. To fill these gaps, we present PyNeon, a versatile, community-oriented Python package designed to streamline the analysis of mobile eye-tracking, motion, and video data from the Neon eye-tracking system (Pupil Labs GmbH). We describe how PyNeon provides accessible APIs for reading, preprocessing, epoching, and exporting Neon data. Furthermore, it supports advanced video processing such as mapping between eye movement data and real-world coordinates and dynamic scanpath estimation. 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