Skip to content

Setting up your machine-learning environment

There are three methods available to set up an environment in which to work on Machine Learning within kdb+/q:

  • with Anaconda
  • with Docker
  • do it yourself

Download via Anaconda

The three KX packages can be downloaded from anaconda.org/kx:

  • kdb
  • embedpy
  • jupyterq

These are available for Linux, Windows and macOS.

They are in a dependency tree. If you install embedpy it will automatically install kdb. If you install jupyterq it will install embedpy and kdb.

The commands are as follows:

conda install -c kx kdb
conda install -c kx embedpy
conda install -c kx jupyterq

At present, the packages work only from the base environment.

Before starting q, run the following commands:

source deactivate base
source activate base

When you first run q it will ask the following questions:

Please provide your email (requires validation):
Please provide your name:
If applicable please provide your company name (press enter for none):

This will then contact the KX license server, which will generate a kc.lic and send an email confirmation link to validate it.

Docker command

1. Install Docker

2. Run embedPy

$ docker run -it --name myembedpy kxsys/embedpy
KDB+ 3.5 2017.11.08 Copyright (C) 1993-2017 Kx Systems
l64/ 4(16)core 7905MB kx 0123456789ab 172.17.0.2 EXPIRE 2018.12.04 bob@example.com KOD #0000000

q)

You can drop straight into Bash with:

$ docker run -it kxsys/embedpy bash
kx@b8279373a1d1:~$ conda info

     active environment : kx
    active env location : /home/kx/.conda/envs/kx
    ...

kx@b8279373a1d1:~$ q
KDB+ 3.5 2018.04.25 Copyright (C) 1993-2018 Kx Systems
l64/ 8()core 64304MB kx b8279373a1d1 172.17.0.3 EXPIRE 2019.05.21 bob@example.com KOD #0000000

q)

Instructions for running headless or with an existing license

Build instructions for the embedPy image

3. Run JupyterQ

docker run --rm -it -p 8888:8888 kxsys/jupyterq

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

Build instructions for the JupyterQ image

Allows Jupyter notebooks to be used within a Docker container.

Do it yourself

  1. Install kdb+
  2. Install embedPy
  3. Install JupyterQ