kig

ArrayBuffer.littleEndian = new Int8Array(new Int16Array([1]).buffer)[0] > 0;

var arrayToNative = function(array, arrayIsLittleEndian) {
  if (!!arrayIsLittleEndian == ArrayBuffer.littleEndian) {
    return array;
  } else {
    return flipArrayEndianness(array);
  }
};

lidopaglia

<#
.SYNOPSIS
   Converts Markdown formatted text to HTML.
.DESCRIPTION
   Converts Markdown formatted text to HTML using the Github API. Output is "flavored" depending on 
   the chosen mode. The default output flavor is 'Markdown' and includes Syntax highlighting and 
   Github stylesheets.
   
   Based on the Ruby version by Brett Terpstra:
   http://brettterpstra.com/easy-command-line-github-flavored-markdown/

k33g

##The Singleton Pattern

class SantaClaus {

	private static uniqueInstance : SantaClaus;
	

bzerangue

<?xml version="1.0" encoding="UTF-8"?>
<!-- 
  ## SOURCE: xe.com
-->
<currency-symbol count="115">
  <entry code="ALL" unicode-decimal="76, 101, 107" unicode-hex="4c, 65, 6b">Albania Lek</entry>
  <entry code="AFN" unicode-decimal="1547" unicode-hex="60b">Afghanistan Afghani</entry>
  <entry code="ARS" unicode-decimal="36" unicode-hex="24">Argentina Peso</entry>
  <entry code="AWG" unicode-decimal="402" unicode-hex="192">Aruba Guilder</entry>
  <entry code="AUD" unicode-decimal="36" unicode-hex="24">Australia Dollar</entry>

jasonrudolph

5 entertaining things you can find with the GitHub Search API

Let's have some command-line fun with curl, [jq][1], and the [new GitHub Search API][2].

Today we're looking for:

• The hottest repositories created in the last week.
• The oldest user accounts with zero followers. (So sad.)
• Issue trends by language.
• Clojure projects defying convention.

joshbeckman

if (window.File && window.FileReader && window.FileList && window.Blob) {
  // Great success!
  function handleJSONDrop(evt) {
    evt.stopPropagation();
    evt.preventDefault();
    var files = evt.dataTransfer.files;
      // Loop through the FileList and read
      for (var i = 0, f; f = files[i]; i++) {
  
        // Only process json files.

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

olmokramer

/(#([0-9a-f]{3}){1,2}|(rgba|hsla)\(\d{1,3}%?(,\s?\d{1,3}%?){2},\s?(1|0?\.\d+)\)|(rgb|hsl)\(\d{1,3}%?(,\s?\d{1,3}%?\)){2})/i

dfinke

Add-Type -AssemblyName PresentationFrameWork

$MainWindow=@'
<Window xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation"
        xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml"
        Topmost="True"
        WindowStartupLocation="CenterScreen"
        Title="PowerSHell Summit Videos" Height="850" Width="1200">
    <Grid>
        <Grid.RowDefinitions>

ovrmrw

using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

using System.Web.Http;
using System.Web.Http.Tracing;
using System.Reflection;
using Owin;