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