Jun 19, 2017
A couple of months back I did a brief writeup of Keybase and what it's good for. I mentioned briefly that it implements a 1-to-n text chat feature, where n>=1. Yes, this means that you can use Keybase Chat to talk to yourself, which is handy for prototyping and debugging code. What does not seem to be very well known is that the Keybase command line utility has a JSON API, the documentation of which you can scan through by issuing the command `keybase chat help api` from a command window. I'm considering incorporating Keybase into my exocortex so I spent some time one afternoon playing around with the API, seeing what I could make it do, and writing up what I had to do to make it work. As far as I know there is no official API documentation anywhere; at least, Argus and I didn't find any. So, under the cut are my notes in the hope that it helps other people work with the Keybase API.
The API may drift a bit, so here are the software versions I used during testing:
Jun 17, 2017
I've been promising myself that I'd do a series of articles about tools that I've incorporated into my exocortex over the years, and now's as good a time as any to start. Rather than jump right into the crunchy stuff I thought I'd start with something that's fairly simple to use, straightforward, and endlessly useful for many purposes - a wiki.
Usually, when somebody brings up the topic of wikis one either immediately thinks of Wikipedia or one of the godsawful corporate wikis that one might be forced to use on a daily basis. And you're not that off the mark, because ultimately they're websites that let one or more people create, modify, and delete articles about just about anything one might be inclined to by using only a web browser. Usually you need to set up or be given an account to log into them because wiki spam is to this day a horrendous problem to fight (I've had to do it as parts of previous jobs, and I wouldn't wish it on my worst enemy). If you've been around a while, when you think of having a wiki you might think of setting up something like WikiWikiWeb or Mediawiki, which also means setting up a server, a database, web server software, the wiki software, configuring everything... and unless you have a big, important project that necessitates it, it's kind of overkill and you go right back to a text file on your desktop. And I don't blame you.
There are other options out there that require much less in the way of overhead that are also nicer than the ubiquitous notes.txt file. For the past couple of years (since 2012.ev at least) I've been using a personal wiki called Tiddlywiki for most of my projects which requires just a fairly modern web browser (if you're using Internet Explorer you need to be running IE 10 or later) and some room on your desktop for another file.
Jun 11, 2017
To keep the complexity of parts of my exocortex down I've opted to not separate everything into larger chunks using popular technologies these days, such as Linux containers (though I did Dockerize the XMPP bridge as an experiment) because there are already quite a few moving parts, and increasing complexity does not make for a more secure or stable system. However, this brings up a valid and important question, which is "How do you restart everything if you have to reboot a server for some reason?"
A valid question indeed. Servers need to be rebooted periodically to apply patches, upgrade kernels, and generally to blow the cruft out of the memory field. Traditionally, there are all sorts of hoops and gymnastics one can go through with traditional initscripts but for home-grown and third party stuff it's difficult to run things from initscripts in such a way that they don't have elevated privileges for security reasons. The hands-on way of doing it is to run a GNU Screen session when you log in and start everything up (or reconnect to one if it's already running). This process, also, can be automated to run when a system reboots. Here's how:
Feb 07, 2017
As I've mentioned a few times in the past, diverse parts of my exocortex monitor many different aspects of the world. One of them, called Ironmonger, constantly data mines the global stock markets looking for anomalies. Ordinarily, Ironmonger only triggers when stock trading events greater than three standard deviations hit the market. On Monday, 6 Feb at 14:50:38 hours UTC-0800 (PST), Ironmonger did an acrobatic pirouette off the fucking handle. Massive trades of three different tech companies (Intel, Apple, and Facebook) his the US stock market within the same thirty second period. By "massive," I mean that 3,271,714,562 shares of Apple, 3,271,696,623 shares of Intel, and 2,030,897,857 shares of Facebook all hit the market at the same time. The time_t datestamps of the transactions were 1486421438 (Intel), 1486421431 (Apple), and 1486421442 (Facebook) (I use time.is to convert them back into organic-readable time/date specifiers). I grabbed some screenshots from the Exocortex console at the time - check them out:
Intel ; Apple ; Facebook
The tall blue slivers at the far right-hand edges of each graph represent the stock trades. I waited a couple of hours and took another set of screenshots (Intel, Apple, Facebook) because the graph had moved on a bit and the transaction spikes were much more visible. While my knowledge of the stock market is limited, I have to admit that I've never seen multi-billion share stock trades happen before. Out of curiosity, I took a look at the historical price per share of each of those stocks to see what those huge offers did to them. The answer, somewhat surprisingly, was "not much." Check out these extracts from Ironmonger's memory: Facebook, Intel, and Apple.
Because I am a paranoid and curious sort, I immediately wondered if there was a correlation with the large spike in the Bitcoin transaction fee earlier that day (at 13:19:16 UTC-0800, to be precise). The answer is... probably not. A transaction fee of 2.35288902 BTC (approximately $2510.93us as of 22:32 hours UTC-0800 on 7 February 2017, as I write this article ahead of time), while a sizeable sum that would certainly guarantee that someone's transaction made it into a block at that very instant does not mean that it was involved. There just isn't enough data, but it stands on its own as another anomaly that day. I wish I knew who put those huge blocks of stock up for sale all at once. The only thing they seem to have in common is that they're all listed on the Singularity Index, which is mildly noteworthy.
Anybody have any ideas?
Feb 04, 2017
A couple of weeks ago I ran into some of the functional limits of my web search bot, a bot that I wrote for my exocortex which accepts English-like commands ("Send me top 15 hits for HAL 9000 quotes.") and runs web searches in response using the Searx meta-search engine on the back end. This is to say that I gave my bot a broken command ("Send hits for HAL 9000 quotes.") and the parser got into a state where it couldn't cope, threw an exception, and crashed. To be fair, my command parser was very brittle and it was only a matter of time before I did something dumb and wrecked it. At the time I patched it with a bunch of if..then checks for truncated and incorrect commands, but if you look at all of the conditionals and ad-hoc error handling I probably made the situation worse, as well as much more difficult to maintain in the long run. Time for a rewrite.
Back to my long-term memory field. What to do?
I knew from comp.sci classes long ago that compilers use things called parsers and grammars to interpret code so that it can be converted into an executable. I also knew that the parser Infocom used in its interactive fiction was widely considered to be the best anyone had come up with in a long time, and it was efficient enough to run on humble microcomputers like the C-64 and the Apple II. For quite a few years I also ran and hacked on a MOO, which for the purposes of this post you can think of as a massive interactive fiction environment that the players can modify as well as play in; a MOO's command parser does pretty much the same thing as Infocom's IF parser but is responsive to the changes the user's make to their environments. I also recalled something called a parse tree, which I sort-of-kind-of remembered from comp.sci but because I'd never actually done anything with them, I only recalled a low-res sketch. At least I had someplace to start from so I turned my rebooted web search bot loose with a couple of search terms and went through the results after work. I also spent some time chatting with a colleague whose knowledge of the linguistics of programming languages is significantly greater than mine and bouncing some ideas off of him (thanks, TQ!)
But how do I do something with all this random stuff?