dingo is a Python package that brings advanced scientific-computing techniques into the hands of developers and researchers. It focuses on modelling metabolic networks — complex systems describing how cells process nutrients and energy — by simulating the full range of possible biochemical flux states. Historically, exploring these possibilities in large-scale networks has been computationally prohibitive. dingo introduces state-of-the-art Monte Carlo sampling algorithms that dramatically speed up these simulations, enabling the analysis of very large models such as Recon3D on a regular personal computer in under a day. With its easy-to-use Python interface and integration within the broader scientific Python ecosystem (e.g. NumPy, Matplotlib), dingo lowers the barrier to entry for studying complex biological systems. This talk will walk the audience through the computational challenges of metabolic modelling, show how dingo leverages Python and efficient sampling to overcome them, and highlight how Python developers and computational biologists alike can contribute to or extend this open-source project. Whether you’re interested in open-source scientific software, computational biology, or high-performance Monte Carlo methods in Python, this talk aims to inspire and provide actionable insight into using and contributing to dingo.