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So far you ve concentrated on retrieving a single document via HTTP or making one update at time. In these cases, it doesn t make much sense to use the asynchronous programming model. However, you ll often want to make many HTTP requests at once, so that you can retrieve and aggregate data from multiple data sources. In these situations, using the F# s asynchronous workflows that you first encountered in 10 s Asynchronous Programming section can seriously improve your application s performance. In fact, you can probably expect to see a bigger performance pay off than when working with the local disk, as you did in 10, because network I/O is generally slower that the local disk. This is because the asynchronous programming model allows us to wait on I/O without blocking a thread, which means the thread can carry on and do other work. Essentially this allows you to wait on multiple I/O completions in parallel. As you parallelize waiting time, you can expect the biggest speed increase from high latency services. Imagine you want to retrieve a list of all your friends, then retrieve a list of all of their friends from the popular social network, twitter. Perhaps you want to do some analysis of this network, and try to find other people that you might know among the friends of your friends. Listing 11-6 shows you how to do this.

CHAPTER 11 LIGHTS, CAMERA, ACTION!

Everyone is present during this time (developers, testers, and customers), so the need for written documentation decreases Costing of the requested features is done immediately and on a feature-by-feature basis..

Listing 11-6. Using HTTP Asynchronously open open open open open open open open System System.IO System.Net System.Text System.Xml System.Xml.XPath System.Globalization Microsoft.FSharp.Control.WebExtensions

import pygame from pygame.locals import * # Import the Model3D class import model3d def resize(width, height): glViewport(0, 0, width, height) glMatrixMode(GL_PROJECTION) glLoadIdentity() gluPerspective(60.0, float(width)/height, .1, 1000.) glMatrixMode(GL_MODELVIEW) glLoadIdentity()

// a record to hold details about a tweeter type Tweeter = { Id: int; Name: string; ScreenName: string; PictureUrl: string; } // turn the xml stream into a strongly typed list of tweeters let treatTweeter name (stream: Stream) = printfn "Processing: %s" name let xdoc = new XPathDocument(stream) let nav = xdoc.CreateNavigator() let xpath = nav.Compile("users/user") let iter = nav.Select(xpath) let items = [ for x in iter -> let x = x : > XPathNavigator let getValue (nodename: string) = let node = x.SelectSingleNode(nodename) node.Value { Id = Int32.Parse(getValue "id"); Name = getValue "name"; ScreenName = getValue "screen_name"; PictureUrl = getValue "profile_image_url"; } ] name, items // function to make the urls of let friendsUrl = Printf.sprintf "http://twitter.com/statuses/friends/%s.xml" // asynchronously get the friends of the tweeter let getTweetters name = async { do printfn "Starting request for: %s" name let req = WebRequest.Create(friendsUrl name) use! resp = req.AsyncGetResponse() use stream = resp.GetResponseStream() return treatTweeter name stream }

The sooner customers can start to use the software, the sooner the customers can receive a return on their investment. Projects that develop systems in small increments prove to be more successful than those that have long delivery dates.

def init(): # Enable the GL features we will be using glEnable(GL_DEPTH_TEST) glEnable(GL_LIGHTING) glEnable(GL_COLOR_MATERIAL) glEnable(GL_TEXTURE_2D) glEnable(GL_CULL_FACE) glShadeModel(GL_SMOOTH) glClearColor(1.0, 1.0, 1.0, 0.0) # white # Set the material glMaterial(GL_FRONT, glMaterial(GL_FRONT, glMaterial(GL_FRONT, glMaterial(GL_FRONT,

// from a single twitter username get all the friends of friends of that user let getAllFriendsOfFriends name = // run the first user synchronously let name, friends = AsyncRunSynchronously (getTweetters name) // only take the first 99 users since we're only allowed 100 // requests an hour from the twitter servers let length = min 99 (Seqlength friends) // get the screen name of all the twitter friends let friendsScreenName = Seqtake length (Seqmap (fun { ScreenName = sn } -> sn) friends) // create asynchronous workflows to get friends of friends let friendsOfFriendsWorkflows = Seqmap (fun sn -> getTweetters sn) friendsScreenName // run this in parallel let fof = AsyncRunSynchronously (AsyncParallel friendsOfFriendsWorkflows) // return the friend list and the friend of friend list friendsScreenName, fof As you can see, the asynchronous part is not too different from its synchronous counterpart.

GL_AMBIENT, (0.0, 0.0, 0.0, 1.0)) GL_DIFFUSE, (0.2, 0.2, 0.2, 1.0)) GL_SPECULAR, (1.0, 1.0, 1.0, 1.0)) GL_SHININESS, 10.0)

This is where the practice of small releases is invaluable. By selecting just enough business functionality and setting that as the target release, the whole XP team has a more visible target. Additionally, small releases allow the XP team to gain a greater sense of accomplishment when compared with projects that take many months or years to reach a release date. Ideally, a release should be due in 30 to 180 days. This is negotiated with the customer during the planning game.

The code needs to be wrapped in the async { .. } workflow, and you need to use an explanation mark (!) when you make the asynchronous call; however, the code is unchanged apart from that: let getTweetters name = async { let req = WebRequestCreate(friendsUrl name) use! resp = reqAsyncGetResponse() use stream = respGetResponseStream() return treatTweeter name stream } When you get the original list of friends, you need to execute a single workflow Because you need to wait for the result of this workflow, you re effectively executing this synchronously You use the AsyncRun function to execute a workflow and wait for the result: let name, friends = AsyncRun (getTweetters name) The other important bit is how you make the calls in parallel.