oxbowlakes

/**
 * Part Zero : 10:15 Saturday Night
 *
 * (In which we will see how to let the type system help you handle failure)...
 *
 * First let's define a domain. (All the following requires scala 2.9.x and scalaz 6.0)
 */

import scalaz._
import Scalaz._

ryanmark

/*
 * Take a set of full height screenshots for a range of screensizes.
 *   phantomjs responsive-screens.js http://www.cnn.com/ png
 *
 * This will create a directory tree in your current directory which
 * mirrors the URL. All files will be named with the current time.
 * You can run this on a cron to build an archive of screenshots.
 **/

var page = new WebPage(),

derpston

# Scatters dots randomly on your terminal as a quick demo of curses.

import curses
import random
import time

window = curses.initscr()

try:
    (h, w) = window.getmaxyx()

gatlin

#!/bin/bash

# source: http://www.haskell.org/pipermail/haskell-cafe/2011-March/090170.html

sudo rm -rf /Library/Frameworks/GHC.framework
sudo rm -rf /Library/Frameworks/HaskellPlatform.framework
sudo rm -rf /Library/Haskell
rm -rf ~/.cabal
rm -rf ~/.ghc
rm -rf ~/Library/Haskell

arosien

import scalaz._
import Scalaz._
import Free._

/** "Pure" interactions with a console. */
sealed trait Console[+A]
case class GetLine[A](k: String => A) extends Console[A]
case class PutLine[A](s: String, a: A) extends Console[A]

object 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

gak

void main(void) 
{ 
    float x,y;
	float ratio = iResolution.y / iResolution.x;
     
	x = gl_FragCoord.x / iResolution.x - 0.5;
	y = gl_FragCoord.y / iResolution.y * ratio - 0.25;
	
	float PI = 3.14159265358979323846264;

justjoheinz

/**
 * Original source:
 * [[https://gist.github.com/oxbowlakes/970717]]
 * 
 * Modifications:
 *  - use scala 7.0.5
 *  - use toValidationNel
 *  - use sequenceU and traverseU instead of the lambda trick
 * 
 * Part Zero : 10:15 Saturday Night

tixxit

import scalaz._

import scala.util.Try

final class X {
  val magic: Int = scala.util.Random.nextInt(10000)
  def isStable: Boolean = magic == 42
}

object Main extends App {

vrischmann

realm=Sonatype Nexus Repository Manager
host=nexus.company.com
user=admin
password=admin123