jupyterq

Jupyter kernel for kdb+. Features include

Syntax Highlighting for q
Code completion for q keywords, .z/.h/.Q/.j namespace functions, and user defined variables
Code help for q keywords and basic help (display and type information) for user defined objects
script like execution of code (mulitline input)
Inline display of charts created using embedPy and matplotlib
console stdout/stderr capture and display in notebooks
Inline loading and saving of scripts into and from notebook cells

Requirements

You can either

There are two ways to install jupyterq on your local machine:

Install the required Python packages with

pip

pip install -r requirements.txt

or with conda

conda install --file requirements.txt

Ensure QHOME is set and you have a working version of q in your PATH, note that jupyter will not pick up bash aliases when starting q, the location of the q executable needs to be in your PATH.
Run the install script

Linux/macOS
```
  ./install.sh
```
Windows
```
 install.bat
```

Download and install either the full Anaconda distribution or Miniconda for Python3.
Use the conda to install jupyterq and it's dependencies

conda install -c kx jupyterq

Ensure you can run q before running jupyterq for the first time, you may need to generate an on demand licence

q
...
q)\\

To run the jupyter console

jupyter console --kernel=qpk

To run the example notebook

jupyter notebook kdb+Notebooks.ipynb

If you have Docker installed you can alternatively run:

docker run -it -p 8888:8888 --name myjupyterq kxsys/jupyterq

For subsequent runs, you will not be prompted to redo the license setup when calling:

docker start -ai myjupyterq

N.B. instructions regarding headless/presets are available

N.B. build instructions for the image are available

See the notebook kdb+Notebooks.ipynb for full interactive examples and explanation, it should be viewable on github.

Documentation is available on the jupyterq homepage.