No need to activate the conda environment. Jupyter kernelspec install /etc/miniconda/envs/xeus-cling/share/jupyter/kernels/xcpp17 -sys-prefix Jupyter kernelspec install /etc/miniconda/envs/xeus-cling/share/jupyter/kernels/xcpp14 -sys-prefix To install the conda xeus-cling kernel directly into Jupyter do the following: jupyter kernelspec install /etc/miniconda/envs/xeus-cling/share/jupyter/kernels/xcpp11 -sys-prefix Inside of the kernels/ directory you will find a few c++ kernels. The path starts with xeus-cling because that's what we named the conda environment earlier. The kernels are located in xeus-cling/share/jupyter/kernels. Thus there will be a subdirectory for each environment which holds all the installed packages. My conda environments were located in /etc/miniconda/envs. Install xeus-cling kernel in the xeus-cling environment created earlier: conda install xeus-cling -c conda-forge -n xeus-cling -yesįind where your conda environments are installed by looking for envs directories in the output of the following command: conda info The following commands are what worked on ubuntu:focalĬreate the environment to install xeus-cling kernel: conda create -n xeus-cling -yes Heres a solution without having to activate the conda environment. C++14Ĭreate a new blank jupyter worksheet and don't forget to change the cell to C++ !! In the bottom bar select the kernel to e.g. Now a message should appear reload kernel, click on the button to do so Select Existing or copy the token into it On the top of the window a list will pop up, looking like Next go to code-insiders and click on the bottom bar Jupyter Server: Remote Start a jupyter notebook from command line (of course in your conda environment described above) jupyter notebook -no-browserĬopy or remember the line with the token, which looks like If you have still problems try the following: Then invoke code (insiders) in your project directory code-insiders. In linux this looks like conda activate xeus-cling # my env for xeus-cling where i compiled cling You have to activate your conda environment and invoke vs-code from it (i use the code insiders edition).
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