Downloading and installing libSBML

We provide ready-to-use installers for many operating systems and programming languages, so most users don’t need to build libSBML themselves (though that’s an option too!). Please use table at right to find the appropriate instructions for your case.

Note: stable releases of libSBML contain support for only the accepted parts of SBML and finalized SBML Level 3 packages, while experimental releases contain code for SBML Level 3 packages that have not been finalized.

MATLAB

For stable releases of libSBML, we provide a unified installer for all versions of MATLAB and all operating systems. The result is ready to run after installation; it does not need compilation, and only requires you tell MATLAB where you placed the files. Here are the steps:

1. Download the distribution archive file.
2. Extract the archive to a folder somewhere on your computer. (Let's refer to this folder as folder.)
3. Start your copy of MATLAB, then do one of the following series of steps.
   Approach #1:
   1. Add folder to your MATLAB path using MATLAB's addPath command.
   2. Verify that it works: change the current directory within your running MATLAB environment to folder and issue the command TranslateSBML('test.xml'). If all is well, the output will be a MATLAB data structure.
   3. Save the changes to your MATLAB path for future use. You can use MATLAB's standard savepath command.
   Approach #2:
   1. On your computer (outside of MATLAB), navigate to folder.
   2. Run the program installSBML, which performs the above steps.

Python

We provide four ways to obtain the libSBML Python interface. Please use whichever one you prefer.

Alternative #1: using Conda

We provide the libSBML Python interface through conda forge. To get the stable release of libSBML using conda, run the following command in a terminal:

conda install -c conda-forge python-libsbml

Alternatively, if you want to install the experimental release of libSBML using conda, run the following command in a terminal:

conda install -c conda-forge python-libsbml-experimental

After this, you should be able to access the Python language interface for libSBML directly from your Python programs by importing it like any other Python module. In other words, import libsbml should work in your Python program.

Alternative #2: using pip from PyPI

First, if you do not have pip or are uncertain if you do, run the following command in a terminal:

sudo python3 -m ensurepip

Then, to install the stable release of libSBML, run the following command:

sudo python3 -m pip install python-libsbml --upgrade

Alternatively, if you want to install the experimental release of libSBML, run the following command:

sudo python3 -m pip install python-libsbml-experimental --upgrade

Note that in either case, the process may take a long time because on some operating system versions, it must install and build dependent libraries. Please be patient. If all goes well, the steps above should result in pip eventually printing the following message to tell you has it finished successfully:

Successfully installed python-libsbml
Cleaning up...

After this, you should be able to access the Python language interface for libSBML directly from your Python programs by importing it like any other Python module. In other words, import libsbml should work in your Python program.

R

We provide installers for the stable version of the libSBML R language interface for Linux, Mac OS X and Windows. Download the version that is appropriate for your situation:

• For Linux and Mac OS X: Download the libSBML R source package from GitHub.

Once you have downloaded the appropriate version, one more step is required to install the libSBML R interface. You can do this step in one of two ways: either using the R graphical interface, or using a terminal/shell command.

Using the R GUI

From the R menu Packages or Packages & Data (depending on your operating system), select the Package Installer item. You will be presented with an interface that lets you install a local binary package. Use that interface to navigate to the directory where you copied the libSBML archive file, and select the archive file for installation.

Using a shell command

Suppose that the path to the libSBML R archive on your computer is archive. Execute the following command in a terminal/shell window (note: not in the R command line interpreter!):

R CMD INSTALL archive

If all goes well, you should see R print messages. If you’re using the source package, it will be something such as the following (the paths on your computer may differ):

* installing to library ‘/Library/Frameworks/R.framework/Versions/3.1/Resources/library’
* installing *binary* package ‘libSBML’ ...
* DONE (libSBML)

whereas if you are using a binary package, the messages will be something like the following instead:

> utils:::menuInstallLocal()
  package ‘libSBML’ successfully unpacked and MD5 sums checked
>

From this point forward, you should be able to call on libSBML functions from within your copy of R. You can test whether the installation was successful by trying the following command in R:

library('libSBML')

If R does not report an error when you execute this command, then the libSBML R interface is probably installed correctly.

Other languages

If no installation package is available for your platform, or you have special requirements for libSBML’s configuration, you can always build libSBML from sources.

1. Download libSBML from our GitHub distribution site.
2. Follow the instructions for configuring, compiling and installing libSBML manually.