Inspired by this approach, we implemented a simple framework of route similarity relying on the NetworkX GED algorithm. The NetworkX GED functionality accepts a bespoke cost function for the node substitution through the parameter 'node subst cost' of the 'graph edit distance' or 'optimized graph edit distance' functions. Here, the cost for deleting and inserting nodes was set to unity, as this is common in literature and corresponds to swapping a node with one of a different type (e.g., Molecule with a Chemical Equation). Otherwise, the cost for node substitution derives from fingerprint-based molecular or reaction similarity, as implemented in RDKit. Since the LinChemIn module exposes the RDKit options, the user can select the most appropriate combination of reaction/molecular fingerprint and similarity metric. By restricting the application to rooted graphs (such as synthetic routes), the 'roots' parameter of the GED function increases the computational efficiency of the algorithms.