corbinbs

#!/usr/bin/env python

"""
A script to query the Amazon Web Services usage reports programmatically.

Ideally this wouldn't exist, and Amazon would provide an API we can use 
instead, but hey - that's life.

Basically takes your AWS account username and password, logs into the
website as you, and grabs the data out. Always gets the 'All Usage Types'

mattgorecki

import websocket
import thread
import time
import sys
from urllib import *

class SocketIO:
	def __init__(self):
		self.PORT = 5000
		self.HOSTNAME = '127.0.0.1'

chandlerprall

THREE.Vector3.prototype.lerp = function ( a, t ) {
	return this.clone().addSelf( a.clone().subSelf( this ).multiplyScalar( t ) );
};

THREE.Vertex.prototype.interpolate = function( other, t ) {
	var v = new THREE.Vertex( this.position.lerp( other.position, t ) );
	v.normal = this.normal.clone();
	return v;
};

g3d

#Mac OS X

Mensch coding font

Apps

• Webkit
• Chrome
• Firefox

dlivingstone

// Simple decorator pattern example
// (c) Daniel Livingstone 2012
// CC-BY-SA

#include <string>
#include <iostream>
using namespace std;

class AbstractNPC {
public:

brandonb927

#!/bin/sh

###
# SOME COMMANDS WILL NOT WORK ON macOS (Sierra or newer)
# For Sierra or newer, see https://github.com/mathiasbynens/dotfiles/blob/master/.macos
###

# Alot of these configs have been taken from the various places
# on the web, most from here
# https://github.com/mathiasbynens/dotfiles/blob/5b3c8418ed42d93af2e647dc9d122f25cc034871/.osx

willurd

Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.

Discussion on reddit.

Python 2.x

$ python -m SimpleHTTPServer 8000

Banus

Mendeley command for Backtick.

How to add this command:

1. Copy the ID of your Gist from the URL. (7619625)

2. Paste the ID into the custom commands field in the Backtick settings. You can easily access the settings by clicking the Backtick icon on the command execution console.

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

neic

\newcommand{\ghost}[1]{\tikz[baseline=.1em,scale=.5]{
  \draw [fill=#1] (0,0) -- (0,.5) arc (+180:0:.3) -- (.6,0) --
  (.5,.15) -- (.4,0) -- (.3,.15) -- (.2,0) -- (.1,.15) -- cycle;
    \coordinate (eye) at (360*rand:.03);
    \foreach \x in {.17,.43}{
      \fill[white] (\x,.5) circle[radius=.1];
      \fill[black] (\x,.5) ++(eye) circle[radius=.05];
    }
}}