py37/jupyterq

Jupyter kernel for kdb+

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

• kdb+>= v3.5 64-bit
• Python >= 3.5
• embedPy

Overview

You can either

• Install jupyterq to run on your local machine; or
• Download or build a Docker image in which to run jupyterq

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

1. Download and install a release

2. Install with Conda - recommended if you are already using Anaconda Python

Install on local machine

Download and install a release

1. Make sure you have installed embedPy

2. Download a release archive from the releases page, and unzip it.

3. Install the required Python packages with

   pip

   pip install -r requirements.txt

   or with conda

   conda install --file requirements.txt

4. 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.

5. Run the install script

   Linux/macOS

     ./install.sh

   Windows

    install.bat
   

Install with Conda

1. Download and install either the full Anaconda distribution or Miniconda for Python3.

2. Use the conda to install jupyterq and it's dependencies

conda install -c kx jupyterq

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

q
...
q)\\

Running after install

To run the jupyter console

jupyter console --kernel=qpk

To run the example notebook

jupyter notebook kdb+Notebooks.ipynb

Run a Docker Image

If you have Docker installed you can alternatively run:

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

Now point your browser at http://localhost:8888/notebooks/kdb%2BNotebooks.ipynb.

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

Using notebooks

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

Documentation

Documentation is available on the jupyterq homepage.