kqlmagic-kernel 0.1.0

'A Jupyter kernel for Kqlmagic.'

Prerequisites

Jupyter Notebook and Kqlmagic

Installation

To install using pip:

pip install kqlmagic_kernel

Add --user to install in the user-level environment instead of the system environment.

To install using conda:

conda config --add channels conda-forge
conda install kqlmagic_kernel
conda install texinfo # For the inline documentation (shift-tab) to appear.
python -m kqlmagic_kernel.install

Kqlmagic Jupyter kernelspec is automatically installed as part of the python package. This location can be found using jupyter kernelspec list. If the default location is not desired, remove the directory for the kqlmagic kernel, and install using python -m kqlmagic_kernel install. See python -m kqlmagic_kernel install --help for available options.

Usage

To use the kernel, run one of:

jupyter notebook
# In the notebook interface, select Kqlmagic from the 'New' menu
jupyter qtconsole --kernel kqlmagic
jupyter console --kernel kqlmagic

This kernel is based on ipykernel, which means it features a standard set of magics (such as %%html). For a full list of magics, run %lsmagic in a cell.

A sample notebook is available online.

Configuration

The kernel can be configured by adding an kqlmagic_kernel_config.py file to the jupyter config path.

The path to the Kqlmagic kernel JSON file can also be specified by creating an KQLMAGIC_KERNEL_JSON environment variable.

Troubleshooting

Kernel Times Out While Starting

If the kernel does not start, run the following command from a terminal:

python -m kqlmagic_kernel.check

This can help diagnose problems with setting up integration with Octave. If in doubt, create an issue with the output of that command.

Kernel is Not Listed

If the kernel is not listed as an available kernel, first try the following command:

python -m kqlmagic_kernel install --user

If the kernel is still not listed, verify that the following point to the same version of python:

which python  # use "where" if using cmd.exe
which jupyter

For details of how this works, see the Jupyter docs on wrapper kernels