What A Difference 18 Years Makes

So, I’m cleaning out some old files this afternoon, and I come across an image of a floppy disk that I stored a few years ago. (I’ve long since digitized and thrown away all floppy media, except for a couple of them that I kept for posterity or for emergency DOS boot disks so I can still play TIE Fighter.)

I mounted the image and discovered something that dates from exactly 18 years ago today: a list of (all!) all the dot-com web servers then in operation on May 31, 1995. Enjoy.

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Good News, Bad News

The good news is that I’m spending some time learning matplotlib, numpy, and Cassandra.

The bad news is that I’m not working on Ancho. Instead, I’m working on a project for Custom Insurance Services. You see, we switched to a new agency management system, which like all major software packages, has its own particular problems. Among other things, its built-in reporting tools are pretty awful. They are both uninformative and unreadable.

Fortunately, it can spit out most of the raw data needed to produce the reports I actually want. So, I’m writing a tool that slurps up the raw data, normalizes it, generates some rollups, and uses those rollups and Sphinx to generate reports in EPUB format with embedded matplotlib charts.

Is that the best way to do it? Who knows? I doubt it, but it’s the way that allows me to spend time learning the other technologies that I need to know how to use.

Ancho’s Next Top (Data) Model

Ancho is for modeling systems, including their uncertainties, so you can simulate the range of probable outcomes. But what would an Ancho model look like? How would you specify your model in code? What features do you need in the framework to make that job easier?

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