Knowledge-Based Environment Dependency Inference for Python Programs

Besides third-party packages, the Python interpreter and system libraries are also critical dependencies of a Python program. In our empirical study, 34% programs are only compatible with specific Python interpreter versions, and 24% programs require specific system libraries. However, existing techniques mainly focus on inferring third-party package dependencies. Therefore, they can lack other necessary dependencies and violate version constraints, thus resulting in program build failures and runtime errors.

This paper proposes a knowledge-based technique named PyEGo, which can automatically infer dependencies of third-party packages, the Python interpreter, and system libraries at compatible versions for Python programs. We first construct the dependency knowledge graph PyKG, which can portray the relations and constraints among third-party packages, the Python interpreter, and system libraries. Then, by querying PyKG with extracted program features, PyEGo constructs a program-related sub-graph with dependency candidates of the three types. It finally outputs the latest compatible dependency versions by solving constraints in the sub-graph. We evaluate PyEGo on 2,891 single-file Python gists, 100 open-source