paulirish

/* bling.js */

window.$ = document.querySelectorAll.bind(document);

Node.prototype.on = window.on = function (name, fn) {
  this.addEventListener(name, fn);
}

NodeList.prototype.__proto__ = Array.prototype;

jareware

Transparent boot2docker on OS X

This is how you can autorun boot2docker on boot, so that you can use docker as you would on Linux, without ever* knowing that the daemon's not running locally.

1. Install VirtualBox & boot2docker (obviously)
2. Create a startup script with Automator
3. Put in /usr/local/bin/boot2docker up && /usr/local/bin/boot2docker shellinit > ~/.boot2docker-shellinit.sh
4. Add echo "export DOCKER_IP=$(boot2docker ip 2>/dev/null)" >> ~/.boot2docker-shellinit.sh if you want the non-standard but very-convenient DOCKER_IP env-var as well (thanks for the suggestion @city41!)
5. Update your .profile or equivalent file with source ~/.boot2docker-shellinit.sh
6. Reboot your machine

beaugunderson

#botally code of conduct

_{based on the #nodejs code of conduct by @izs}

tl;dr If you’re a mean butt you get kicked out. This is not negotiable.

• Sexist, heteronormative, racist, and other offensive remarks are not allowed. (Cursing is allowed, but never targeting another user, and never in a hateful or sexually explicit manner.)
• Remarks that make any of the ops go “Hm, that’s inappropriate”, whether on the above list or not: also not allowed.
• You get a warning.
• If the warning is not taken seriously, you might get a second sterner warning in PM, if you’re lucky, and the op is feeling generous, and this is the first time. But don’t count on that.

tsiege

ANNOUNCEMENT

I have moved this over to the Tech Interview Cheat Sheet Repo and has been expanded and even has code challenges you can run and practice against!






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debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

briancavalier

function keepTrying(otherArgs, promise) {
	promise = promise||new Promise();
	
	// try doing the important thing
	
	if(success) {
		promise.resolve(result);
	} else {
		setTimeout(function() {
			keepTrying(otherArgs, promise);