A Static Type Inference for Python

Dynamic languages, like Python, are attractive because they guarantee that no correct program is rejected prematurely. However, this comes at a price of losing early error detection, and making both code optimization and certification harder tasks when compared with static typed languages. Having the static certification of Python programs as a goal, we developed a static type inference system for a subset of Python, known as RPython. Some dynamic features are absent from RPython, nevertheless it is powerful enough as a Python dialect and exhibits most of its main features. Our type inference system tackles with almost all language constructions, such as object inheritance and subtyping, polymorphic and recursive functions, exceptions, generators, modules, etc., and is itself written in Python.