2017/05/31 by Pierre Fernique, Fernique, Pierre, Christophe Pradal +1
Computer Science · Decision Sciences · #Computational Physics and Python Applications #FOS: Computer and information sciences #Parallel Computing and Optimization Techniques #Scientific Computing and Data Management #Software Engineering (cs.SE) #cs.SE
paper · pdf · doi:10.48550/arxiv.1705.11000
arxiv created 2017/05/31 · openalex publication_date 2017/05/31 · arxiv updated 2017/06/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Most of Python and R scientific packages incorporate compiled scientific libraries to speed up the code and reuse legacy libraries. While several semi-automatic solutions exist to wrap these compiled libraries, the process of wrapping a large library is cumbersome and time consuming. In this paper, we introduce AutoWIG, a Python package that wraps automatically compiled libraries into high-level languages using LLVM/Clang technologies and the Mako templating engine. Our approach is automatic, extensible, and applies to complex C++ libraries, composed of thousands of classes or incorporating modern meta-programming constructs.