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xeus-cling-cmake-setup

DISCLAIMER: This repository is still in an experimental state. It's core functionality is implemented and e.g. used by this project but things may still fail in more general scenarios. You are welcome to give it a try and report your issues though.

xeus-cling provides an implemenation of a Jupyter Kernel for C++ based on the Clang/LLVM C++ interpreter cling. Interpreting C++ in jupyter has great potential e.g. in rapid prototyping and in teaching.

Working with external libaries in xeus-cling requires setting up the include and library paths for the external dependencies with #pragma directives. Putting these directly into the notebook is not ideal for several reasons:

  • They make the notebook quite unreadable
  • They scare beginners
  • They contain build-specific paths, making a distribution of the notebook impossible

This project goes an alternative route of solving the problem to set up xeus-cling with external dependencies: Assuming that you are using CMake to build your project anyway, it provides a CMake extension that generates a xeus-cling kernel configuration into the build directory. This configuration can be installed into your jupyter environment.

Prerequisites

  • A working installation of xeus-cling. The currently preferred way is by using anaconda.
  • Your project needs to build shared libraries (e.g. by setting BUILD_SHARED_LIBS=ON in CMake)
  • Your project needs to be able to successfully build with Clang 5.

How to use it in your code.

This project should be easy to integrate into your project, as its implementation is provided as one single file: Copy XeusClingSetup.cmake into your project and include it into your CMake build system by adding this line to your CMakeLists.txt (preferrably to the top level one):

include(XeusClingSetup.cmake)

If your project makes use of git submodules, you can alternatively add this repository as a submodule and do:

add_subdirectory(xeus-cling-cmake-setup)

After doing this, a function xeus_cling_setup is available in CMake. You can pass CMake targets, include directories, libraries and compile flags to the function to make them available in the generated jupyter kernel configuration:

xeus_cling_setup(
  TARGETS mylibrary
)

It is recommended to work with CMake targets only, but include directories and libraries can also be specified manually (see below for the full signature of xeus_cling_setup).

A kernel.json file will be generated into your build directory. You can install this kernel specification by building the CMake target install_kernelspec or you can manually do so using the jupyter kernelspec install command. Note that in either case, the Conda environment where xeus-cling is installed needs to be activated first.

Documentation

The CMake function xeus_cling_setup allows for many more parameters than shown in above minimal example:

xeus_cling_setup(
  [TARGETS target1 [target2 ...]]
  [INCLUDE_DIRECTORIES inc1 [inc2 ...]]
  [LINK_LIBRARIES lib1 [lib2 ...]]
  [LIBRARY_DIRECTORIES dir1 [dir2 ...]]
  [COMPILE_OPTIONS flag1 [flag2 ...]]
  [COMPILE_DEFINITIONS def1 [def2 ...]]
  [SETUP_HEADERS header1 [header2 ...]]
  [DOXYGEN_TAGFILES tagfile1 [tagfile2 ...]]
  [DOXYGEN_URLS url1 [url2 ...]]
  [KERNEL_LOGO_FILES file1 [file2]]
  [KERNEL_NAME name]
  [CXX_STANDARD 11|14|17]
  [REQUIRED]
)

A detailed description of the parameters can be found at the top of the XeusClingSetup.cmake file.

Limitations

Licensing

XeusClingSetup.cmake is licensed under the MIT license. The license text and copyright statement are provided within the file, so you can just copy it into your project.