However, the rapid development of Python packages for chemistry has been accompanied by increasing complexity in managing software dependencies, a crucial aspect for ensuring consistent and accurate execution of chemical software. Traditional solutions like package managers and virtual environments have only partially addressed these issues, often struggling with Figure : Depiction of the workflow followed by rNets. First, the energies of the compounds, transition states and/or concentrations are collected into .csv data files from simulations. Together with the configuration files, rNets is used to generate a .dot file containing the plotting instructions for the graph. Finally, Graphviz is used to compute the energy or concentrationbased plot.