Note: Credit goes to Uwe for his excellent blog post on how to setup C++ environment for Apache Arrow

As a start, we create a conda environment with all non-C++ dependencies and also install Jupyter Lab from conda-forge.

# Create a new conda environment
conda create -n xeus python=3.6 numpy six setuptools cython pandas \
    pytest cmake rapidjson snappy zlib brotli jemalloc lz4-c zstd ninja \
    jupyterlab -c conda-forge
source activate xeus

As the next step, we will install the gcc-6 compiler from QuantStack which we will use. Additionally, we install the boost-cpp build from QuantStack that was already built with gcc-6. We also set the environment variables CC and CXX so that the new compiler is picked up automatically by the build tools.

conda install gcc-6 boost-cpp -c QuantStack
export CC=${CONDA_PREFIX}/bin/gcc
export CXX=${CONDA_PREFIX}/bin/g++

As the last of the external dependencies, we install the actual interactive environment. For the C++ support, we install the interactive C++ compiler cling and the C++ kernel for Jupyter Notebook xeus-cling from the QuantStack channel.

conda install cling -c QuantStack -c conda-forge
conda install xeus-cling -c QuantStack -c conda-forge

After starting Jupyter Lab with jupyter lab, you should now see two additional kernels: xeus C++11 and xeus C++14. You can use either of them to use write interactive C++ programs.