Modelling planetary magnetospheres is essential to develop understanding of how these dynamic regions of space behave and respond to forcing from both internal and external sources of mass, momentum and energy. Obtaining an exact solution for the governing equations describing these complex systems is very difficult, it is therefore necessary to construct simplified computational simulations to investigate the impact of these forcing sources. The size of planetary magnetospheres, especially at the outer planets, presents additional complications when creating models of these regions as important dynamics occur on spatial scales ranging from planetary radii down to much smaller kinetic ion and electron levels. Such modelling challenges are present in simulating bulk plasma transport in Jupiter's inner and middle magnetosphere, where plasma flows from Io's plasma torus radially outwards. The process of radial transport is attributed to the centrifugal-interchange instability, analogous to the Rayleigh-Taylor instability but with centrifugal force replacing gravity. In order to capture the broadest range of dynamics, as well as efficiently utilise computational resources, a hybrid approach is often taken to modelling the magnetospheric plasma. Treating ion constituent species of the plasma as kinetic charged particles and the electrons as a fluid, hybrid modelling is able to capture large-scale flow dynamics as well as interactions between particles. In this poster, a description of progress towards prototyping a hybrid Jovian plasma transport model in Python is provided. Whilst most models of this type are written in C/C++ or Fortran for performance, the aim in this project is to prototype physical effects to be incorporated into an optimised implementation. Writing a version in a modern accessible language such as Python also has pedagogical value. Included are descriptions of the main loop used to iterate the plasma both spatially and temporally and the visualisation techniques used to examine the results obtained.