libSBML Python API 5.8.0
Sarah Keating, Akiya Jouraku, Frank Bergmann, and Ben Bornstein designed and wrote most of the software, with contributions from Gordon Ball, Bill Denney, Christoph Flamm, Akira Funahashi, Ralph Gauges, Martin Ginkel, Alex Gutteridge, Stefan Hoops, Michael Hucka, Totte Karlsson, Moriyoshi Koizumi, Ben Kovitz, Machné, Nicolas Rodriguez, Lucian Smith, and many others in the SBML community. Michael Hucka wrote most of this libSBML user and API documentation.
This manual describes the Python application programming interface (API) of libSBML, an open-source (LGPL) library for writing and manipulating the Systems Biology Markup Language (SBML). This version of libSBML supports all releases of SBML up through Level 3 Version 1 Core Release 1. For more information about SBML, please visit http://sbml.org on the Internet. Please report bugs and other issues with libSBML using the tracker at http://sbml.org/Software/libSBML/issue-tracker.
Note to readers: Most of this manual is generated automatically from the C++ source code of libSBML. Owing to imperfections in the conversion software, it is not as complete as the C++ API manual. If you encounter undocumented components, you may wish to check the corresponding text in the C++ API manual.
The libSBML Python library makes much of this API documentation accessible using the Python interactive help system. As an example, try typing
help(SBMLDocument) to a Python interpreter (after having imported the libsbml library).
To get started with libSBML, you may find the following sections of this manual helpful:
You can use the navigation bar, table of contents and search facilities of this manual to locate specific documentation about the libSBML API.
Please note: article citations are crucial to our academic careers. If you use libSBML and you publish papers about your software, we ask that you please cite the libSBML paper:
Bornstein, B. J., Keating, S. M., Jouraku, A., and Hucka M. (2008) LibSBML: An API Library for SBML. Bioinformatics, 24(6):880-881.This and other projects of the SBML Team have been supported by the following organizations: the National Institutes of Health (USA) under grants R01 GM070923 and R01 GM077671; the International Joint Research Program of NEDO (Japan); the JST ERATO-SORST Program (Japan); the Japanese Ministry of Agriculture; the Japanese Ministry of Education, Culture, Sports, Science and Technology; the BBSRC e-Science Initiative (UK); the DARPA IPTO Bio-Computation Program (USA); the Army Research Office's Institute for Collaborative Biotechnologies (USA); the Air Force Office of Scientific Research (USA); the California Institute of Technology (USA); the University of Hertfordshire (UK); the Molecular Sciences Institute (USA); the Systems Biology Institute (Japan); and Keio University (Japan).
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