A Trading Engine

So a Wall Street company contacts you, they need a new trading platform running on iOS devices. As it is a trading platform, you define an enum for trades.

First Draft

enum Trades {

     case buy(stock: String, amount: Int, stockPrice: Float)

     case sell(stock: String, amount: Int, stockPrice: Float)

}

You were also handed the following API to handle trades. Notice how sell orders are just negative amounts.

/**

  - parameter stock: The stock name

  - parameter amount: The amount, negative number = sell, positive = buy

*/

func process(stock: String, _ amount: Int) {

     print (\"\(amount) of \(stock)\")

}

The next step is to process those trades. You see the potential for using pattern matching and write this:

let aTrade = Trades.buy(stock: \"APPL\", amount: 200, stockPrice: 115.5)



switch aTrade {

case .buy(let stock, let amount, _):

     process(stock, amount)

case .sell(let stock, let amount, _):

     process(stock, amount * -1)

}

// Prints \"buy 200 of APPL\"

Swift lets us conveniently only destructure / extract the information from the enum that we really want. In this case only the stock and the amount.

Awesome, you visit Wall Street to show of your fantastic trading platform. However, as always, the reality is much more cumbersome than the beautiful theory. Trades aren't trades you learn.

• You have to calculate in a fee which is different based on the trader type.
• The smaller the institution the higher the fee.
• Also, bigger institutions get a higher priority.

They also realized that you'll need a new API for this, so you were handed this:

func processSlow(stock: String, _ amount: Int, _ fee: Float) { print(\"slow\") }

func processFast(stock: String, _ amount: Int, _ fee: Float) { print(\"fast\") }

Trader Types

So you go back to the drawing board and add another enum. The trader type is part of every trade, too.

enum TraderType {

case singleGuy

case company

} 



enum Trades {

     case buy(stock: String, amount: Int, stockPrice: Float, type: TraderType)

     case sell(stock: String, amount: Int, stockPrice: Float, type: TraderType)

}

So, how do you best implement this new restriction? You could just have an if / else switch for buy and for sell, but that would lead to nested code which quickly lacks clarity - and who knows maybe these Wall Street guys come up with further complications. So you define it instead as additional requirements on the pattern matches:

let aTrade = Trades.sell(stock: \"GOOG\", amount: 100, stockPrice: 666.0, type: TraderType.company)



switch aTrade {

case let .buy(stock, amount, _, TraderType.singleGuy):

     processSlow(stock, amount, 5.0)

case let .sell(stock, amount, _, TraderType.singleGuy):

     processSlow(stock, -1 * amount, 5.0)

case let .buy(stock, amount, _, TraderType.company):

     processFast(stock, amount, 2.0)

case let .sell(stock, amount, _, TraderType.company):

     processFast(stock, -1 * amount, 2.0)

}

The beauty of this is that there's a very succinct flow describing the different possible combinations. Also, note how we changed .buy(let stock, let amount) into let .buy(stock, amount) in order to keep things simpler. This will destructure the enum just as before, only with less syntax.

Guards! Guards!

Once again you present your development to your Wall Street customer, and once again a new issue pops up (you really should have asked for a more detailed project description).

• Sell orders exceeding a total value of $1.000.000 do always get fast handling, even if it's just a single guy.
• Buy orders under a total value of $1.000 do always get slow handling.

With traditional nested if syntax, this would already become a bit messy. Not so with switch. Swift includes guards for switch cases which allow you to further restrict the possible matching of those cases.

You only need to modify your switch a little bit to accommodate for those new changes

let aTrade = Trades.buy(stock: \"GOOG\", amount: 1000, stockPrice: 666.0, type: TraderType.singleGuy)



switch aTrade {

case let .buy(stock, amount, _, TraderType.singleGuy):

     processSlow(stock, amount, 5.0)

case let .sell(stock, amount, price, TraderType.singleGuy)

     where price*Float(amount) > 1000000:

     processFast(stock, -1 * amount, 5.0)

case let .sell(stock, amount, _, TraderType.singleGuy):

     processSlow(stock, -1 * amount, 5.0)

case let .buy(stock, amount, price, TraderType.company)

     where price*Float(amount) < 1000:

     processSlow(stock, amount, 2.0)

case let .buy(stock, amount, _, TraderType.company):

     processFast(stock, amount, 2.0)

case let .sell(stock, amount, _, TraderType.company):

     processFast(stock, -1 * amount, 2.0)

}

This code is quite structured, still rather easy to read, and wraps up the complex cases quite well.

That's it, we've successfully implemented our trading engine. However, this solution still has a bit of repetition; we wonder if there're pattern matching ways to improve upon that. So, let's look into pattern matching a bit more.