HDD: highlighting the value of disconnecting, idea gestation and general enjoyment since your next holiday:
A wealth of information is tucked away in Etsy’s Engineering Talks - by the people who build and run Etsy. They cover development, DevOps, security, testing, continuous deployment, configuration management, and engineering culture (among others).
This keyboard works by generating Waveform Audio file data dynamically, converting it into a base64-encoded dataURI, and subsequently playing it using the HTML5 audio element from within your web browser.
Karma is the preeminent cross-browser test framework. It is built in the style of JSTestDriver (remote browsers controlled via HTTP) but in node.js instead of Java. It also overcomes a number of JSTestDriver’s fundamental issues – namely that errors in the code under test do not affect the stability of the runner. Karma is fast, lightweight and extensible. Through its diverse plugin ecosystem it supports any testing framework (Jasmine, Mocha, Qunut, etc), any browser (including any browser on BrowserStack), and a number of great reporters.
I’ve taken advantage of that plugin architecture to write a BDD-style story reporter for Karma. It’s useful to be able to indicate the layout and hierarchy of tests, making tests more readable and self-descriptive. Any failing test and its parent suite blocks are marked red, passes are green and slow tests are reported in yellow (unless they fail, when they are red too).
karma-story-reporter is released under the MIT license and can be installed via
npm install karma-story-reporter --save-dev
Source is available on GitHub.
I was given a copy of this book by its author at a conference a few years ago, and can safely say it distills some of the community’s best programming advice into its 97 chapters.
It’s available in wiki format.
A fascinating insight into Neural Networks, with some excellent visualisations at The Nature of Code.
In this chapter, we’ll begin with a conceptual overview of the properties and features of neural networks and build the simplest possible example of one (a network that consists of a single neuron). Afterwards, we’ll examine strategies for creating a “Brain” object that can be inserted into our Vehicle class and used to determine steering. Finally, we’ll also look at techniques for visualizing and animating a network of neurons.
It contains demonstrations of a basic class, classical inheritance, Resig inheritance and a deeply intertwined Inception class! Make sure you zoom out or use a widescreen monitor for full effect.