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In the past decade, astrophysical simulations have increased dramatically in both scale and sophistication, and the typical size of the datasets produced has grown accordingly.   However, the software tools for analyzing such datasets have not kept pace, such that one of the primary barriers to exploratory investigation is simply manipulating the data.   This problem is particularly acute for users of the popular smoothed particle hydrodynamics (SPH) code \textsc{gadget} \citep{SpringelYoshidaWhite2001,Springel2005}.   Both \textsc{gadget} and \textsc{gizmo} \citep{Hopkins2015}, which outputs data in uses  the same data storage  format, are widely used to investigate a range of astrophysical problems; unfortunately this also leads to fractionation of the data storage format as each research group modifies the output to suit its needs. This state of affairs has historically forced significant duplication of effort, with individual research groups separately developing their own unique analysis scripts to perform similar operations.  Fortunately, the issue of data management and analysis is not endemic to astronomy, and the resulting overlap with the needs of the broader scientific community and the industrial community at large provides a large pool of scientific software developers to tackle these common problems.