Pythran: Enabling Static Optimization of Scientific Python Programs

Pythran is a young open source static compiler that turns modules written in a subset of Python into native ones. Based on the fact that scientific modules do not rely much on the dynamic features of the language, it trades them in favor of powerful, eventually inter procedural, optimizations. These include detection of pure functions, temporary allocation removal, constant folding, Numpy ufunc fusion and parallelization, explicit thread-level parallelism through OpenMP annotations, false variable polymorphism pruning, and automatic vector instruction generation such as AVX or SSE.

In addition to these compilation steps, Pythran provides a C++ runtime library that leverages the C++ STL to provide generic containers, and the Numeric Template Toolbox (NT2) for Numpy support. It takes advantage of modern C++11 features such as variadic templates, type inference, move semantics and perfect forwarding, as well as classical ones such as expression templates.

The input code remains compatible with the Python interpreter, and output code is generally as efficient as the annotated Cython equivalent, if not more, without the backward compatibility loss of Cython. Numpy expressions run faster than when compiled with numexpr, without any change of the original code.