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Doing things from scratch is often an occasion to think about what can be done better, faster or more elegantly. For his PhD project Kevin decided to write his own ARPES analysis software in python. While doing so, he realized that the problem of fast visualization of 3+ dimensional data had already been solved in the medical field. Doctors and surgeons require tools to quickly analyze the multidimensional results of CT and MRI scans. To that end, optimized libraries have already been created. Kevin made use of this fact and adapted the libraries to the needs of ARPES data analysis. The result is the probably fastest ARPES visualization tool to date. With the core code standing, the next steps are the implementation of common analysis routines as well as creation of user-friendly interfaces. To speed up this process and to provide a service to the community, the data is freely available on github [https://github.com/kuadrat/arpys] and everyone is warmly encouraged to take part in the future development.