Kst - Visualize your data • Download • Source Code

Kst - Source Code

Getting the code

  • Pre-packaged source code can be found at SourceForge.
  • Source code is hosted primarily on KDE's git repository.
    • If you are a KDE developer, the repository can be checked out (RW) from:
      "git clone git@git.kde.org:kst-plot".
    • or, if you aren't, read only from:
      "git clone git://anongit.kde.org/kst-plot".
  • The KDE repository is mirrored automatically every 5 minutes to GitHub. Note that all commits should go to KDE git. If you don't have a KDE developer account you can provide patches and send them to the mailing list or work on a GitHub branch and make it publicly available.
    • Browse or fork the Kst2 code at GitHub.
    • If you're more confortable which svn, GitHub also offers svn access.
    • Clone with
      "git clone https://github.com/Kst-plot/kst.git".


To compile Kst 2, Qt libraries are the only required dependency. Versions 4.x and 5.x should work fine, though version 5.x requires an explicit cmake switch. The recommended method is to use the excellent QtCreator IDE in combination with CMake.
When using this combination, all you have to do is download the source code and the tools, and then go to the File->Open menu in Qt Creator and open the CMakeLists.txt file in the cmake/ subdir or in the root directory.

  1. Starting with version 2.0.4, it may not work out-of-the box with qmake (see this thread on the mailing list for the required changes or use revision 1253670). Qmake will very likely be deprecated at some point in the near future.
  2. Even though they are not required dependencies, you may want to check for the libraries listed in the next section prior to compiling Kst, as they will give you some benefits.
  3. Python scripting is a compile-time option. Check cmake flags -Dkst_python=1 and -Dkst_python_build=1

Links to used libraries

Kst uses a number of open-source libraries:

  • The optional GNU Scientific Library, on which a lot of very useful data analysis plugins are based - a should-have!
  • The optional GetData library, which provides support for files in the Dirfile format
  • The optional NetCdf library, which provides support for files in the netCDF format
  • The optional muParser library, which is used in the general non-linear fitting plugin
  • The optional matio library, which is used to read Matlab binary files

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