A weather forecasting center in India was faced with a situation where in-house diagnostic capability had hit a plateau. With legacy code no longer maintainable and resources stretched thin due to an impending transition to a new forecast model, a solution was needed. In this talk we present the use of Python in putting together a model diagnostics framework in order to perform routine diagnostics and give scientists the tools to enhance their research capabilities. The use of available python modules and development of new capabilities with the aim of simplifying the learning curve for end users will be described.