Recovering network structure from binary co-occurrence data is a problem encountered across NLP, epidemiology, manufacturing, and recommender systems; yet there is a lack of shared tools, metrics, or common benchmarks to compare and improve techniques. This paper presents three interoperable Python libraries to address this need.