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Graph representations of programs are commonly a central element of machinelearning for code research. We introduce an open source Python librarypython_graphs that applies static analysis to construct graph representationsof Python programs suitable for training machine learning models. Our libraryadmits the construction of control-flow graphs, data-flow graphs, and composite``program graphs'' that combine control-flow, data-flow, syntactic, and lexicalinformation about a program. We present the capabilities and limitations of thelibrary, perform a case study applying the library to millions of competitiveprogramming submissions, and showcase the library's utility for machinelearning research.

A Library for Representing Python Programs as Graphs for Machine Learning