One thing I’ve always envied in other languages is package management. Python has pip, Node.js has npm, R has CRAN, ruby has gems…the list goes on. For a kdb+ dev, the situation is a little different. For a start, there’s much less open source (or closed source, for that matter) code available to be used in our projects. And when there are bits and pieces available, they’re not always written in a way that easily integrates into other code. We end up copying & pasting code into our code base, making it trickier to get (or contribute) upstream changes.

For a while there have existed a few options for easing the pain of loading other people’s code in your project; options such as the excellent qutil from Dan Nugent. In short, qutil provides a nice, standardised way of packaging code (i.e. a directory with an init.q file), and also a standardised way of organising & loading these packages (i.e. in a directory pointed to by an env var, and loading them with .utl.require function). There are a couple of other options (require.q, qpm), but I prefer qutil.

So that leaves one thing missing that the other languages have; an easy to use command line installer for packages with a central repo. I had thought for a while it would be really nice to have such a thing for q packages; I even toyed with the idea of building such a thing. But when kx announced the availablity of kdb+, jupyterq & embedPy on Anaconda, I realised that Anaconda (which I had previously thought was “just for python”) provided a cross-platform, language agnostic package manager in the form of conda.

So I started packaging some q packages for installation with conda. One of these packages is qutil itself, which sets up the package loading code within the conda environment. Other packages I have packaged are dependent on this, so you shouldn’t have to install it directly, it’ll automatically be set up when you install another package.

I deliberately did not make any of my packages dependent on the kx kdb package - while this is a nice, easy way to get 64-bit kdb+ up & running, it is on-demand only & only for Mac & Linux; Anaconda itself works fine on Windows, and 32-bit (here’s hoping that kx add a Windows version soon, and 32-bit). So the q packages installed in this way will work with either Anaconda kdb or system kdb (installed via traditional means). UPDATE: kx have now added Windows releases of kdb on Anaconda cloud; still 64-bit on-demand only

The easiest way to get up & running is to install miniconda (a minimal Anaconda distribution) and then use conda install to install some of my packages, for example:

jonny@kodiak ~ $ wget
## allow script to download
jonny@kodiak ~ $ sh
## accept the agreement etc.
jonny@kodiak ~ $ export PATH=/home/jonny/miniconda3/bin:$PATH       # add miniconda to PATH
jonny@kodiak ~ $ source activate base                               # activate base conda env
(base) jonny@kodiak ~ $ conda install -c jmcmurray req              # install reQ package & dependencies
## accept prompt to install
(base) jonny@kodiak ~ $ q                                           # start q & test newly install pkg
KDB+ 3.5 2018.04.25 Copyright (C) 1993-2018 Kx Systems
l64/ 4(16)core 7360MB jonny kodiak EXPIRE 2019.05.21 KOD #4160315

args   | (`symbol$())!()
headers| `Accept`Connection`Host`User-Agent!("*/*";"close";"";"kdb..
origin | ""
url    | ""

Over the next few weeks, I hope to release a bunch more packages, and I really hope that we are at the beginning of kdb+ going far more mainstream and building a much larger open source community, with lots of packages available for use in our various projects.

I’ll post more about creating conda packages for q code in a future blog post, but for those interested you can check my conda-recipes repo containing the “recipes” used to build most of my conda packages.