I've taken an interest in building new old window sashes. That is, traditional wooden double-hung windows, as you'd find in any home in America before about 1940. This little essay contains some of my notes on things I have learned about the process.
Last week, the US's National Science Board capped its funding for giant telescopes at $1.6 billion . This may sound like a staggering amount of money - and it is - but it's not likely enough to build the next generation of telescopes, which are estimated to cost $3 billion or more.
Over the last four months, I have been working on a Python library for working with data. The library is called quivr , and I think of it as an answer to a bunch of problems that I found when trying to build robust, maintainable systems and services on top of Numpy and Pandas data structures.
description: I found it surprisingly tricky to get good information on how to set up lsp-mode to work with a Python virtual environment. Here's my solution.
Summary : Steve Jobs's NeXT computer company made a keyboard in 1988. With no prior electronics experience, I tried to get it to work over USB. To do so, I had to go way deeper than I ever expected - all the way back over 100 years to broadcast radio standards from the 1920s. I learned tons and tons, and had a lot of fun.
I work on astronomical data pipelines, and a lot of our data gets shipped around in Avro . It's often a lot of data, like many terabytes, and with complex schemas. And because I'm working on astronomy software, nearly everything is written in Python, the lingua franca of the scientific computing world.
Last time , I discussed the New York Times Spelling Bee, and presented three solutions for it. We had a naive solver, a trie solver, and a bitmask solver. The trie was fastest, then the bitmask, then the naive solution.
While taking care of my newborn son, I've had a lot of time on my hands. A chunk of that time has been on puzzles, and a chunk of it has been on thinking about algorithms to solve the puzzles quickly.