Computer-aided synthesis planning (CASP) is a field of intense research that can provide insight and accelerate the synthesis of novel compounds, both in early discovery and late-stage development . One particular area of CASP is retrosynthesis analysis in which the aim is to predict the necessary steps to synthesize a compound, i.e. a synthetic route (see Figure ). Such methods date back to the 60's and the early work of Corey , although the research has intensified in the last decade due to the increased interest in machine learning and artificial intelligence. At the heart of retrosynthesis analysis is a method that is capable of predicting disconnections on a compound and thereby producing precursors. Such methods are typically referred to as one-step retrosynthesis or single-step retrosynthesis. The precursors produced by the one-step retrosynthesis can then be further broken down recursively until a set of conditions are met. Such iterative methods are typically referred to as multi-step retrosynthesis. Typically, the stop conditions are that a precursor is found in a database of purchasable compounds, i.e. a stock, or that a maximum number of disconnections has been applied. One-step retrosynthesis methods have received the greatest amount of attention: there is a plethora of methods described in the literature that uses a diverse range of methods to extract synthesis rules, cheminformatic representations, neural network architectures, sampling techniques, etc. [see e.g. . For the practitioner that wants to use a method for predictions, or for a researcher developing a novel method, there are several comparisons for a subset of the available methods. In fact, once a novel method is developed it is customary to benchmark it against other methods using a common set of known reactions. The US patent office (USPTO) extracts provided by Lowe is the de-facto standard for comparing single-step retrosynthesis method, as it is one of few open-source datasets of chemical reactions. However, there more than one curated subset of the dataset used , which is a complication. Furthermore, there has not been a survey published showing all one-step methods side by side, so it is still difficult to understand the range of available methods.