ror, scala, jetty, erlang, thrift, mongrel, comet server, my-sql, memchached, varnish, kestrel(mq), starling, gizzard, cassandra, hadoop, vertica, munin, nagios, awstats
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package pack | |
import java.net.{HttpURLConnection, URL} | |
import scala.collection.immutable._ | |
object RandomUrlResponse extends App{ | |
var urlStatusMap = SortedMap[String,Int]() | |
val url = "http://www.randomwebsite.com/cgi-bin/random.pl" | |
var con : HttpURLConnection = _ |
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""" | |
Simple algorithm to download all the egghead.io videos in highest-quality from YouTube. | |
Run from the directory you want the videos to appear. Renames them so that they have the video number + omit the repetitive "Egghead.io - AngularJS -" text. | |
Installing dependency: | |
$ pip install git+https://github.com/NFicano/pytube#egg=pytube | |
""" | |
from pytube import YouTube #, exceptions as YTD_exceptions |
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package pack; | |
import java.util.Scanner; | |
/** | |
* Created by asus kelebek on 13.7.2015. | |
*/ | |
public class crossStars { | |
public static void main( String args[] ) | |
{ |
#Introduction to Properties
<script type="text/jsx">
/*** @jsx React.DOM */
var APP = React.createClass({
getDefaultProps:function(){
return {
txt:'gdfgdfgdf',
cat:0
React is a UI Library in Javascript. Created by the folks at Facebook, it helps with creating webcomponents, but better than the webcomponents implemented in HTML5. React allows you to create composable view components, utilizing a unidirectional data flow, or one-way data flow. This differs to Angular that has a data binding components, which is two directional between controller and view.
Note: I call elements components, but now they're really called elements. Take that in consideration when I use the word component.
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import akka.actor.ActorSystem | |
import akka.stream.ActorFlowMaterializer | |
import akka.stream.scaladsl.{Flow, Sink, Source} | |
import scala.collection.immutable | |
import scala.util.Random | |
object InputCustomer { | |
def random():InputCustomer = { | |
InputCustomer(s"FirstName${Random.nextInt(1000)} LastName${Random.nextInt(1000)}") |
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import org.apache.spark.graphx._ | |
import org.apache.spark._ | |
import org.apache.spark.rdd.RDD | |
import org.apache.spark.SparkContext | |
object BristolAdjacency { | |
def main(args: Array[String]): Unit ={ | |
lazy val conf = { | |
new SparkConf(false) |