Simon Willison’s Weblog


Tuesday, 14th November 2017

tuxracer-web. Brilliant Docker hack from David Cooper: just run “docker run -p 8008:80 dtcooper/tuxracer-web” to get Tux Racer (the 3D game) running in your browser, on top a cunning mix of the noVNC HTML5 VNC client and icecast for sound. # 11:28 pm

We are actively developing cross datacenter replication (internally we are calling it “cross cluster replication” so you will likely see it referred to this in the future but of course this is subject to change). I can not give a timeframe, but it is one of the top features on the Elasticsearch roadmap.

Jason Tedor # 10:40 pm

nginx proxy-cache-lock (via) Crucially important feature hidden away in the nginx documentation: proxy_cache_lock enables request coalescing, or dog-pile protection: it means that if a hundred simultaneous requests all suffer the same cache miss, only one request is made to the backend and the answer is then sent back to all hundred requests at once. I’ve leaned heavily on this feature in Varnish for years—useful to know that nginx has the same capability. # 9:53 pm

pillow-simd (via) A “friendly fork” of the Python Pillow image library that takes advantage of SIMD operations on certain CPUs to obtain massive speed-ups—they claim 16 to 40 times faster than ImageMagick. # 9:42 pm

Using SVG as placeholders — More Image Loading Techniques. This is such a good idea: generate a tiny SVG placeholder for an image, and display that until the image itself has loaded. This article explores potential ways of generating those SVGs in some depth. # 7:19 pm

Datasettes · simonw/datasette. I’m collecting examples of datasette-powered APIs on the project wiki. # 7:39 am

Datasette for Polar Bears. I found a fun dataset of Polar Bear ear tag tracking data put out by the USGS Alaska Science Center and deployed it using datasette in just a couple of minutes—here’s how I did it. # 5:41 am

How to train your own Object Detector with TensorFlow’s Object Detector API (via) Dat Tran built a TensorFlow model that can detect raccoons! Impressive results, especially given it was only trained on 200 raccoon images from Google Image search. # 4:24 am