text: Socket.IO is probably the best known of all the real-time web frameworks. In combination with Node.js, it's responsible for a significant increase in awareness of the benefits of 'the evented web', real-time data and real-time interactive user experiences.
  In this tutorial, I'll take a look at what's in the new Socket.IO 1.0, and show how it can be used to build an app for real-time analytics.
  To keep things simple we'll capture the page URL and a couple of browser capabilities using Modernizr (modernizr.com). That information will be sent to the server using a Socket.IO connection.
  The server will do some basic analysis on that data, store it and publish the data to a dashboard. The dashboard will receive the information and display it using the Epoch charting library (fastly.github.io/epoch).
  Getting started
  For this app you're going to need at least Node.js v0.10.25 installed. You also need to download the 'getting started' zip. Unzip that archive and you'll see a node_modules directory with all the Node.js modules we need for this tutorial.
  We'll put all our client-side code in the public directory – there's a bower_components directory in there, containing all the JavaScript libraries our app will depend on. There is also a dashboard directory where we'll build the dashboard frontend.
  Let's get Socket.IO set up and create a test page that connects to the running server. First create an index.js file in the root of your working directory. Since we want to serve a dashboard, we'll start by creating a web server using Express, one of the most popular Node.js web server packages.
  var express = require( ‘express’ ); var app = express(); app.use( express.static( __dirname + ‘/public’) ); var server = require( ‘http’ ).Server( app ); server.listen( 3000, function(){ console.log( ‘listening on *:3000’ ); } );
  In index.js we're using Express' express.static function to declare that all files in the public folder can be served directly. Let's create a capture.html in the public directory.
  Run node index.js in your working directory from a command prompt and navigate to in your browser. Make sure you see that file being served. Now we can add Socket.IO to index.js.
  var server = require( ‘http’ ).Server( app ); var io = require( ‘socket.io’ )( server ); io.on( ‘connection’, function( socket ) { console.log( ‘We have a connection!’ ); } );
  A reference to the running server is gained via require ('http').Server( app) and Socket.IO can then attach to that server using var io = require('socket.io')(server). We also bind to the connection event using io.on('connection, function() {} ) and log to the connection when the event is triggered. This event signifies that a connection from a client has been detected.
  Finally, we need to add some JavaScript to capture. html to connect to Socket.IO.
  <script src=”/bower_components/socket.io-client/socket.io.js”></script> <script> var socket = io( 'localhost:3000' ); socket.on( 'connect', function() { console.log( 'connected' ); } ); </script>
  To achieve this we've included the Socket.IO client library, created a new socket connection using io( 'localhost:3000' ) and bound to the connect event so we know when the server connection has been established.
  Reload capture.html and open up the JavaScript console to check for the connected log message. Look at the prompt you used to execute node index.js and you'll see We have a connection!
  Capturing data
  With the basics in place we can now start capturing data from the client. We'll use capture.html as a way of developing and testing this functionality.
  The information we're going to capture, and ultimately display, is as follows: that a connection has been established, what page URL the user is viewing and a couple of the user's browser capabilities such as Touch and HTML5 Video support.
  <script src=”/bower_components/socket.io-client/socket.io.js”></script> <script src=”/bower_components/modernizer/modernizr.js”></script> <script> var socket = io( 'localhost:3000/capture' ); socket.on( 'connect', function() { var data = { url: window.location.href, touch: Modernizr.touch, video: Modernizr.video }; socket.emit( 'client-data', data ); } );
  The URL we're connecting to is localhost:3000/ capture where /capture is an example of a Socket.IO namespace (netm.ag/names-258). Namespaces are handy for partitioning data – here, they identify a communication channel for capturing data.
  In the connect event callback we create a data object upon which we store all the information our app wants; the page URL is stored on data.url and Modernizr is used when capturing values for data.touch and data.video . Finally, the information is sent to the server using socket.emit( 'client-data', data ).
  We're now sending all the data we want to capture to the server. Let's update the server code in index.js to prove it's getting that data:
  var io = require( 'socket.io' )( server ); var capture = io.of( '/capture' ); capture.on( 'connection', function( socket ) { socket.on( 'client-data', function( data ) { console.log( data ); } ); } );
  You'll notice that the server code has also been updated to now reference the /capture namespace. It's important that we use a namespace or we'll also count connections to our dashboard in the stats when we create it.
  We bind to the client-data event, which mirrors the event we emit on the client. If you restart the node process and refresh capture.html you'll see the information that's been captured is logged to the command prompt.
  Storing stats data
  On the server we want to keep track of connections and associated data so we can calculate stats.
  var socketData = {}; var stats = { connections: 0, touch: 0, video: 0, pages: {} }; var capture = io.of( '/capture' ); capture.on( 'connection', function( socket ) { ++stats.connections; socket.on( 'client-data', function( data ) { socketData[ socket.id ] = data; stats.touch += ( data.touch? 1 : 0 ); stats.video += ( data.video? 1 : 0 ); var pageCount = stats.pages[ data.url ] || 0; stats.pages[ data.url ] = ++pageCount; } ); } );
  First, the connection count is incremented when a user connects to the /capture namespace. The socketData variable is used to map a socket to its associated stats data using a unique socket.id .
  The storage takes place in the client-data event callback. touch and video values are incremented if supported by the client. The number of connections on each page is stored by URL in the stats.pages property.
  We also need to update the stats as connections are lost. Within the connection callback bind to the disconnect event on the socket object:
  stats.pages[ data.url ] = ++pageCount; } ); socket.on( 'disconnect', function() { --stats.connections; stats.touch -= ( socketData[ socket.id ].touch? 1 : 0 ); stats.video -= ( socketData[ socket.id ].video? 1 : 0 ); --stats.pages[ socketData[ socket.id ].url ]; delete socketData[ socket.id ]; } );
  In the same way that we incremented values in the connection callback we decrement values in the disconnect callback.
  Publishing the data
  Now that all the data is stored, we want to publish it so that a dashboard can consume and display the stats. Since all the data is already stored in the stats object, we just need to publish it. For this, we'll use a /dashboard namespace.
  var stats = { connections: 0, touch: 0, video: 0, pages: {} }; var dashboard = io.of( '/dashboard' ); dashboard.on( 'connection', function( socket ) { socket.emit( 'stats-updated', stats ); } );
  The /dashboard namespace is referenced and when a new connection is detected the current stats are emitted to the newly connected socket only.
  We also need to trigger an event to all dashboard clients whenever the stats update – for example, after a client-data event is received and processed, or when a /capture connection triggers the disconnect event. To do that, simply emit a stats-updated event on the dashboard namespace at the end of the appropriate callbacks:
  dashboard.emit( 'stats-updated', stats );
  Real-time analytics dashboard
  The only thing that's left now is to build the dashboard. If you open public/dashboard/index.html you'll see it includes the Epoch charts library, its stylesheet and dependencies.
  Within that file you'll also find various element placeholders with clearly named id attributes for our real-time analytics charts: visitors area chart for connection count, pages bar chart for popular pages, touch and video gauges for touch support and video element support respectively.
  A file js/dashboard.js is also referenced from index.html. Open this up and initialise the Epoch charts.
  var visitors = $('#visitors').epoch( { type: 'time.area', axes: ['left', 'bottom', 'right'], data: [ { values: [ { time: Date.now()/1000, y: 0 } ] } ], } ); var pages = $( '#pages' ).epoch( { type: 'bar' } ); var touch = $( '#touch' ).epoch( { type: 'time.gauge' } ); var video = $( '#video' ).epoch( { type: 'time.gauge' } );
  The server is already publishing the stats as soon as it has them, so in order to receive that data we need to subscribe to the /dashboard namespace and bind to the stats-updated event.
  Finishing off
  Finally, we need to extract the data we want from the update and tell our charts to update.
  var video = $( '#video' ).epoch( { type: 'time.gauge' } ); var dashboard = io( 'localhost:3000/dashboard' ); dashboard.on( 'stats-updated', function( update ) { visitors.push( [ { time: Date.now()/1000, y: update.connections } ] ); var pagesData = []; for( var url in update.pages ) { pagesData.push( { x: url, y: update.pages[ url ] } ); } pages.update( [ { values: pagesData } ] ); touch.update( update.touch / update.connections || 0 ); video.update( update.video / update.connections || 0 ); } );
  To update the visitors chart we reference update.connections and update the visitors chart. We loop over update.pages and format the data where x is the page URL and y is the number of connections on that page. The touch and video gauges are updated with a value between 0 and 1 based on the ratio of stat versus connections.
  With everything in place you can now restart the node process and load dashboard/index.html to see the dashboard. Open in one or more tabs to start capturing data and watch the captured data instantly displayed in the dashboard.
  Conclusion
  We've only scratched the surface of what can be achieved with this application and with the new tools and features in Socket.IO 1.0. But hopefully this tutorial has given you a taster of just how powerful and easy it can be to use real-time technologies in your web apps.!