Intrinsic to collection change notifications, items can be notified by add, update and remove events. If ordering is supported a collection will support a move notification. Of course Dynamic Data supports these. Yet something which is often overlooked is data or functions of data are sometimes by necessity mutable. How can a collection which notifies respond to mutable changes?

To deal with this scenario, dynamic data introduces the concept of an Evaluate notification. This notification forms part of a change set and tells a consumer an item needs to be re-assessed or re-evaluated. This may effect things like filtering or sorting of an item. I feel a concrete example best illustrates this concept. Suppose we have the following function:

Func<Trade,bool> isNearToMarketPrice = trade => return Math.Abs(trade.PercentFromMarket) <= 1 %

Where PercentFromMarket is a calculation which is recalculated with each and every market data tick. Using standard linq a list of near to market trades can be retrieved as follows.

var nearToMaketTrades = myListOfTrades.Where(isNearToMarketPrice);

The manifest problem with this query is it pull based only and has no means of observing when the market price has been recalculated, or alternatively how can re-evaluation be forced. Based on practical experience of dealing with this kind problem I introduced multiple means of injecting the evaluate command into a dynamic data stream. Here I will use a filter controller illustrated in a previous blog and we will apply it to the trade service here.

In summary any of the controllers in dynamic data are used to inject commands and meta data into a stream. For this example we need a dynamic filter which is applied to a stream of trades.

//create a filter controller and set it's filter
var filter = new FilterController<Trade>();
filter.Change(trade => Math.Abs(trade.PercentFromMarket) <= percentFromMarket());

//create a stream of live trades where the trade matches the above filter
var filteredByPercent  = myTradeService.Trades
                         .Connect(trade=>trade.Status==TradeStatus.Live)
                         .Synchronize(locker)
                         .Filter(filter)

The filter controller has an overload to force re-evaluation.

filter.Revalue() // to reevaluate all
// or
filter.Reevaluate(Func<T,bool> itemSelector) //to re-evaluate selected items

The only missing element is when do we invoke re-evalulation. We have 2 choices. Either the service which calculates market prices provides a notification of trades which have been re-calculated or we poll on a period. Option 1 would be suitable for algo trading where everything must happen preferably with zero latency but for simplicity in the example we will poll as follows.

//re-evaluate filter periodically
var reevaluator = Observable.Interval(TimeSpan.FromMilliseconds(250))
                         .Subscribe(_ => filter.Reevaluate());

And that is that. We have a live stream of trades, where closed trades are automatically filtered out from the source and the filter controller constantly re-applies to ensure only trades near to the market are included in the result.   And as ever what is beginning to become my catch phrase – that is easy!

After wrapping the function into a cold observable, here’s the final code.

public IObservable<IChangeSet<Trade, long>> Query(Func<uint> percentFromMarket)
{
    if (percentFromMarket == null) throw new ArgumentNullException("percentFromMarket");
    return Observable.Create<IChangeSet<Trade, long>>
	(observer =>
	 {
	     var locker = new object();
	     Func<Trade,bool> nearToMaketTrades = trade => Math.Abs(trade.PercentFromMarket) <= percentFromMarket();
	     var filter = new FilterController<Trade>(nearToMaketTrades);

	     //re-evaluate filter periodically
	     var reevaluator = Observable.Interval(TimeSpan.FromMilliseconds(250))
		 .Synchronize(locker)
		 .Subscribe(_ => filter.Reevaluate());

	     //filter on live trades matching % specified
	     var subscriber = _tradeService.Trades
		 .Connect(trade=>trade.Status==TradeStatus.Live)
		 .Synchronize(locker)
		 .Filter(filter)
		 .SubscribeSafe(observer);

	     return new CompositeDisposable(subscriber, filter, reevaluator);
	 });
}

This observable will form part of a future post where I want to build the foundation of an auto trading system.

But for now, in a few lines of code (see NearToMarketViewer.cs) we can put the data onto the screen.