/ Machine Learning

Jupyter kernel for the Python programming language

Jupyter kernel for the Python programming language

xeus-python

xeus-python is a Jupyter kernel for Python based on the native implementation of the Jupyter protocol xeus.

Usage

Launch the Jupyter notebook with jupyter notebook or Jupyter lab with jupyter lab and launch a new Python notebook by selecting the xpython kernel.

Code execution and variable display:

Basic code execution

Output streams:

Streams

Input streams:

Input

Error handling:

Erro handling

Inspect:

Inspect

Code completion:

Completion

Rich display:

Rich display

And of course widgets:

Widgets
Widgets binary

Installation

xeus-python has been packaged for the conda package manager.

To ensure that the installation works, it is preferable to install xeus-python in a fresh conda environment. It is also needed to use a miniconda installation because with the full anaconda you may have a conflict with the zeromq library which is already installed in the anaconda distribution.

The safest usage is to create an environment named xeus-python with your miniconda installation

conda create -n xeus-python
conda activate xeus-python # Or `source activate xeus-python` for conda < 4.6

Installation directly from conda

Then you can install in this environment xeus-python and its dependencies

conda install xeus-python notebook -c conda-forge

Installation from source

Or you can install it from the sources, you will first need to install dependencies

conda install cmake xeus nlohmann_json cppzmq xtl pybind11 jedi pygments notebook -c conda-forge

Then you can compile the sources

cmake -D CMAKE_PREFIX_PATH=your_conda_path -D CMAKE_INSTALL_PREFIX=your_conda_path -D PYTHON_EXECUTABLE=`which python`
make && make install

Trying it online

To try out xeus-python interactively in your web browser, just click on the binder
link:

Binder

Documentation

To get started with using xeus-python, check out the full documentation

http://xeus-python.readthedocs.io/

What are the advantages of using xeus-python over ipykernel (IPython kernel)?

Check-out this blog post for the answer: https://blog.jupyter.org/a-new-python-kernel-for-jupyter-fcdf211e30a8.
Long story short:
xeus-python does not cover 100% of the features of ipykernel. For examples, IPython magics are not supported yet by xeus-python. However:

  • xeus-python is a lot lighter than ipykernel and IPython combined, which makes it a lot easier to implement new features on top of it. Our next goal is to augment the protocol to implement a Python debugger in JupyterLab.
  • xeus-based kernels are more versatile in that one can overload e.g. the concurrency model. This is something that Kitware’s SlicerJupyter project takes advantage of to integrate with the Qt event loop of their Qt-based desktop application.

Dependencies

xeus-python depends on

xeus-python xeus xtl cppzmq nlohmann_json pybind11 jedi pygments six
master >=0.22.0,<0.23 >=0.6.5,<0.7 ~4.3.0 >=3.6.1,<4.0 >=2.2.4,<3.0 >=0.13.3,<0.14.0 >=2.3.1,<3.0.0
0.4.0 >=0.22.0,<0.23 >=0.6.5,<0.7 ~4.3.0 >=3.6.1,<4.0 >=2.2.4,<3.0 >=0.13.3,<0.14.0 >=2.3.1,<3.0.0
0.3.2 >=0.21.1,<0.22 >=0.6.5,<0.7 ~4.3.0 >=3.6.1,<4.0 >=2.2.4,<3.0 >=0.13.3,<0.14.0 >=2.3.1,<3.0.0
0.3.1 >=0.21.1,<0.22 >=0.6.5,<0.7 ~4.3.0 >=3.6.1,<4.0 >=2.2.4,<3.0 >=0.13.3,<0.14.0 >=2.3.1,<3.0.0
0.3.0 >=0.21.1,<0.22 >=0.6.5,<0.7 ~4.3.0 >=3.6.1,<4.0 >=2.2.4,<3.0 >=0.13.3,<0.14.0 >=2.3.1,<3.0.0
0.2.2 >=0.19.2,<0.20 >=0.6.4,<0.7 ~4.3.0 >=3.6.1,<4.0 >=2.2.4,<3.0 >=0.13.3,<0.14.0 >=2.3.1,<3.0.0
0.2.1 >=0.18.1,<0.19 >=0.5.2,<0.6 ~4.3.0 >=3.3.0,<4.0 >=2.2.4,<3.0 >=0.13.1,<0.14.0 >=2.3.1,<3.0.0
0.2.0 >=0.18.1,<0.19 >=0.5.2,<0.6 ~4.3.0 >=3.3.0,<4.0 >=2.2.4,<3.0 >=0.13.1,<0.14.0 >=2.3.1,<3.0.0
0.1.5 >=0.18.1,<0.19 >=0.5.2,<0.6 ~4.3.0 >=3.3.0,<4.0 >=2.2.4,<3.0 >=0.13.1,<0.14.0 >=2.3.1,<3.0.0
0.1.4 >=0.18.1,<0.19 >=0.5.2,<0.6 ~4.3.0 >=3.3.0,<4.0 >=2.2.4,<3.0 >=0.13.1,<0.14.0 >=2.3.1,<3.0.0
0.1.3 >=0.18.1,<0.19 >=0.5.2,<0.6 ~4.3.0 >=3.3.0,<4.0 >=2.2.4,<3.0 >=0.13.1,<0.14.0 >=2.3.1,<3.0.0
0.1.2 >=0.18.1,<0.19 >=0.5.2,<0.6 ~4.3.0 >=3.3.0,<4.0 >=2.2.4,<3.0 >=0.13.1,<0.14.0 >=2.3.1,<3.0.0 >=1.12.0,<2.0.0
0.1.1 >=0.18.1,<0.19 >=0.5.2,<0.6 ~4.3.0 >=3.3.0,<4.0 >=2.2.4,<3.0 >=0.13.1,<0.14.0 >=2.3.1,<3.0.0
0.1.0 >=0.18.1,<0.19 >=0.5.2,<0.6 ~4.3.0 >=3.3.0,<4.0 >=2.2.4,<3.0 >=0.13.1,<0.14.0 >=2.3.1,<3.0.0
0.0.4 >=0.18.1,<0.19 >=0.5.2,<0.6 ~4.3.0 >=3.3.0,<4.0 >=2.2.4,<3.0 >=0.13.1,<0.14.0
0.0.3 >=0.17.0,<0.18 >=0.5.0,<0.6 ~4.3.0 >=3.3.0,<4.0 >=2.2.4,<3.0 >=0.13.1,<0.14.0
0.0.2 >=0.16.0,<0.17 >=0.4.0,<0.5 ~4.3.0 >=3.3.0,<4.0 >=2.2.4,<3.0
0.0.1 >=0.15.0,<0.16 >=0.4.0,<0.5 ~4.3.0 >=3.3.0,<4.0 >=2.2.4,<3.0

GitHub