Performance of the primary PyPi service has been so bad lately that it’s become very disruptive. Tasks that used to take a few seconds will now churn along for 15-20 minutes or longer before completing, which is incredibly frustrating. I first went looking to see if there was a PyPi mirror infrastructure, like we see with CPAN for Perl or CTAN for Tex (and similarly for most Linux distributions). There is apparently no such beast,

The SYM-1 is a 6502-based single-board computer produced by Synertek Systems Corp in the mid 1970’s. I’ve had one floating around in a box for many, many years, and after a recent foray into the world of 6502 assembly language programming I decided to pull it out, dust it off, and see if it still works. The board I have has a whopping 8KB of memory, and in addition to the standard SUPERMON monitor it has the expansion ROMs for the Synertek BASIC interpreter (yet another Microsoft BASIC) and RAE (the “Resident Assembler Editor”).

Let’s say you have a couple of sensors attached to an ESP8266 running MicroPython. You’d like to sample them at different frequencies (say, one every 60 seconds and one every five minutes), and you’d like to do it as efficiently as possible in terms of power consumption. What are your options? If we don’t care about power efficiency, the simplest solution is probably a loop like this: import machine lastrun_1 = 0 lastrun_2 = 0 while True: now = time.

We’re all looking for ways to keep ourselves occupied these days, and for me that means leaping at the chance to turn a small problem into a slightly ridiculous electronics project. For reasons that I won’t go into here I wanted to generate an alert when a certain WiFi BSSID becomes visible. A simple solution to this problem would have been a few lines of shell script to send me an email…but this article isn’t about simple solutions!

We’ve had some wacky weather recently. In the space of a week, the temperature went from a high of about 75°F to a low around 15°F. This got me to thinking about what constitutes “normal” weather here in the Boston area, and in particular, how common it is to have a string of consecutive days in which the high temperature stays below freezing. While this was an interesting question in itself, it also seemed like a great opportunity to learn a little about Pandas, the Python data analysis framework.