JupyterLite loader for Xeus kernels
- JupyterLab >= 4.0.0
To install the extension, execute:
pip install jupyterlite_xeusTo load a xeus-python kernel with a custom environment, create an environment.yml file with xeus-python and the desired dependencies. Here is an example with numpy as a additional dependency:
name: xeus-lite-wasm
channels:
- https://repo.mamba.pm/emscripten-forge
- conda-forge
dependencies:
- xeus-python
- numpyTo build JupyterLite, run the following command where environment.yml is the path to the file you just created
jupyter lite build --XeusAddon.environment_file=some_path/to/environment.ymlTo load a xeus-lua or xeus-sqlite kernel you can
do the same as above, just with
dependencies:
- xeus-luaor
dependencies:
- xeus-sqliteNote that xeus-sqlite and xeus-lua do not support additional dependencies yet.
To build JupyterLite, run again:
jupyter lite build --XeusAddon.environment_file=environment.ymlTo create a deployment with multiple kernels, you can simply add them to the environment.yml file:
name: xeus-lite-wasm
channels:
- https://repo.mamba.pm/emscripten-forge
- conda-forge
dependencies:
- xeus-python
- xeus-lua
- xeus-sqlite
- numpyWhen developing a xeus-kernel, it is very useful to be able to test it in JupyterLite without having to publish the kernel to emscripten-forge. Therefore, you can also use a local environment / prefix to build JupyterLite with a custom kernel.
This workflow usually starts with creating a local conda environment / prefix for the emscripten-wasm32 platform with all the dependencies required to build your kernel (here we install dependencies for xeus-python).
micromamba create -n xeus-python-dev \
--platform=emscripten-wasm32 \
-c https://repo.mamba.pm/emscripten-forge \
-c conda-forge \
--yes \
"python>=3.11" pybind11 nlohmann_json pybind11_json numpy pytest \
bzip2 sqlite zlib libffi xtl pyjs \
xeus xeus-liteThis depends on your kernel, but it will look something like this:
# path to your emscripten emsdk
source $EMSDK_DIR/emsdk_env.sh
WASM_ENV_NAME=xeus-python-dev
WASM_ENV_PREFIX=$MAMBA_ROOT_PREFIX/envs/$WASM_ENV_NAME
# let cmake know where the env is
export PREFIX=$WASM_ENV_PREFIX
export CMAKE_PREFIX_PATH=$PREFIX
export CMAKE_SYSTEM_PREFIX_PATH=$PREFIX
cd /path/to/your/kernel/src
mkdir build_wasm
cd build_wasm
emcmake cmake \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_FIND_ROOT_PATH_MODE_PACKAGE=ON \
-DCMAKE_INSTALL_PREFIX=$PREFIX \
..
emmake make -j8 installYou will need to create a new environment with the dependencies to build the JupyterLite site.
# create new environment
micromamba create -n xeus-lite-host \
jupyterlite-core
# activate the environment
micromamba activate xeus-lite-host
# install jupyterlite_xeus via pip
python -m pip install jupyterlite-xeusWhen running jupyter lite build, we pass the prefix option and point it to the local environment / prefix we just created:
jupyter lite build --XeusAddon.prefix=$WASM_ENV_PREFIXTo copy additional files and directories into the virtual filesystem of the xeus-lite kernels you can use the --XeusAddon.mount option.
Each mount is specified as a pair of paths separated by a colon :. The first path is the path to the file or directory on the host machine, the second path is the path to the file or directory in the virtual filesystem of the kernel.
jupyter lite build \
--XeusAddon.environment_file=environment.yml \
--XeusAddon.mounts=/some/path/on/host_machine:/some/path/in/virtual/filesystemCreate the conda environment with conda/mamba/micromamba (replace micromamba with conda or mamba according to your preference):
micromamba create -f environment-dev.yml -n xeus-lite-devActivate the environment:
micromamba activate xeus-lite-devpython -m pip install -e . -v --no-build-isolationSee RELEASE.
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