SWIG

An extensible compiler for creating scriptable scientific software. Scripting languages such as Python and Tcl have become a powerful tool for the construction of flexible scientific software because they provide scientists with an interpreted problem solving environment and they form a modular framework for controlling software components written in C, C++, and Fortran. However, a common problem faced by the developers of a scripted scientific application is that of integrating compiled code with a high-level interpreter. This paper describes SWIG, an extensible compiler that automates the task of integrating compiled code with scripting language interpreters. SWIG requires no modifications to existing code and can create bindings for eight different target languages including Python, Perl, Tcl, Ruby, Guile, and Java. By automating language integration, SWIG enables scientists to use scripting languages at all stages of software development and allows existing software to be more easily integrated into a scripting environment.


References in zbMATH (referenced in 49 articles )

Showing results 1 to 20 of 49.
Sorted by year (citations)

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  1. Karl Wette: SWIGLAL: Python and Octave interfaces to the LALSuite gravitational-wave data analysis libraries (2020) arXiv
  2. Ruiz-Gironés, Eloi; Roca, Xevi: Imposing boundary conditions to match a CAD virtual geometry for the mesh curving problem (2019)
  3. Siggel, Martin; Kleinert, Jan; Stollenwerk, Tobias; Maierl, Reinhold: TiGL: an open source computational geometry library for parametric aircraft design (2019)
  4. Ansmann, Gerrit: Efficiently and easily integrating differential equations with JiTCODE, JiTCDDE, and JiTCSDE (2018)
  5. DeGroot, Christopher T: WEdiff: A Python and C++ package for automatic differentiation (2018) not zbMATH
  6. Jain, Abhinandan: An analytical workbench for system level multibody dynamics (2018)
  7. Karl Wette; Reinhard Prix; David Keitel; Matthew Pitkin; Christoph Dreissigacker; John T. Whelan; Paola Leaci: OctApps: a library of Octave functions for continuous gravitational-wave data analysis (2018) not zbMATH
  8. Kulshreshtha, K.; Narayanan, S. H. K.; Bessac, J.; MacIntyre, K.: Efficient computation of derivatives for solving optimization problems in R and Python using SWIG-generated interfaces to ADOL-C (2018)
  9. Richard Beare; Bradley Lowekamp; Ziv Yaniv: Image Segmentation, Registration and Characterization in R with SimpleITK (2018) not zbMATH
  10. Ahmed Attia, Adrian Sandu: DATeS: A Highly-Extensible Data Assimilation Testing Suite (2017) arXiv
  11. Coelho, L.P.: Jug: Software for Parallel Reproducible Computation in Python (2017) not zbMATH
  12. Erika Tudisco; Edward Andò; Rémi Cailletaud; Stephen A.Hall: TomoWarp2: A local digital volume correlation code (2017) not zbMATH
  13. Langtangen, Hans Petter; Linge, Svein: Finite difference computing with PDEs. A modern software approach (2017)
  14. Pierre Fernique, Christophe Pradal: AutoWIG: Automatic Generation of Python Bindings for C++ Libraries (2017) arXiv
  15. Roberto Souza, Letícia Rittner, Rubens Machado, Roberto Lotufo: iamxt: Max-tree toolbox for image processing and analysis (2017) not zbMATH
  16. König, Marcel; Radtke, Lars; Düster, Alexander: A flexible C++ framework for the partitioned solution of strongly coupled multifield problems (2016)
  17. Linaro, Daniele; Storace, Marco: \textscBAL: a library for the \textitbrute-force analysis of dynamical systems (2016)
  18. Yallop, Jeremy; Sheets, David; Madhavapeddy, Anil: Declarative foreign function binding through generic programming (2016)
  19. Pommereau, Franck: SNAKES: a flexible high-level Petri nets library (tool paper) (2015)
  20. Śmigaj, Wojciech; Betcke, Timo; Arridge, Simon; Phillips, Joel; Schweiger, Martin: Solving boundary integral problems with BEM++ (2015)

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Further publications can be found at: http://www.swig.org/doc.html