DDD with DSL monad in fsharp

What is DDD?

Lets check a description from Wikipedia.

Domain-driven design (DDD) is an approach to software development for

complex needs by connecting the implementation to an evolving model. The premise of domain-driven design is the following:

placing the project’s primary focus on the core domain and domain logic

basing complex designs on a model of the domain

initiating a creative collaboration between technical and domain experts to iteratively refine a conceptual model that addresses particular domain problems

DDD was described by Eric Evans in Domain-Driven Design: Tackling Complexity in the Heart of Software If we dig deeper then we will find a term Ubiquitous Language.

Short description from Martin Fowler

Ubiquitous Language is the term Eric Evans uses in Domain Driven Design for

the practice of building up a common, rigorous language between developers

and users. This language should be based on the Domain Model used in the software - hence the need for it to be rigorous, since software doesn’t cope well with ambiguity.

So in short it is all about language between domain experts and developers.

Usually it means that in our code we have to abstract our code from infrastructure details and describe everything in terms of a business model. Main pattern in OOP languages is to use Interface as abstraction and encapsulate infrastructure details in a class which implements an interface. All other classes depends only from other interfaces, so we can easy swap implementation. Main patterns for composition are Dependency injection and Inversion of control.

There are a lot of tutorials how to do DDD in c#, but what about f#? Actually we can use the same way in fsharp, but this way has some drawbacks and we probably could find better way to do that. I found several excellent articles about how to do ddd in fsharp.

For example A different look at service design and Domain Driven Design with the F# type System. They describe how to model domain in terms of functions and types. But we will try to go deeper.

DSL

So ddd is about languages. In programming languages we could build our domain language as external or internal dsl. Internal dsls are better because we could use all existing tools of a host language. Internal dsls could be shallow or deep. Shallow embedding means that we describe our domain in types and have fixed interpretation of the data. It is not very useful, because for testing we want to use a fake interpreter and in production use an optimized interpreter. So we want to build deep internal dsl. How? We could represent all operations as abstract types and compose abstract computations with a computation builder. But we also want to abstract not only from implementation but also from function effects. DDD with interfaces has this problem. For example dependency without effect.

type MyInterface = abstract member Add : int -> int -> int type Customer ( dependency : MyInterface ) = member this . AddOneTo x = dependency . Add 1 x |> printfn "%d"

Now we want to add numbers asynchronously. And we have to change everything.

type MyInterface = abstract member Add : int -> int -> Async < int > type Customer ( dependency : MyInterface ) = member this . AddOneAndPrint x = async { let ! r = dependency . Add 1 x printfn "%d" r return () }

Lets start. We need to represent our abstract operations as data types. But how? In short our command will look like a request to a server(interpreter). Request is a type for representation of a command tag and input params

type Request < ' i > = ' i type Dsl = Add of Request < int * int >

But we also need a way to compose commands together. So interpreter needs a way to execute a command and invoke some function which will take command result and return a new command to proceed or some kind of stop signal like return something command. Lets do that.

type Request < ' i , ' o , ' k > = ' i * ( ' o -> ' k )

And for composition we need some bind function which will compose some request with a function which will take output of a command and produce a new one. Internally it will use bind function of continuation type ‘k.

let bindRequest bind f ( s , k ) = s , fun v -> bind ( k v , f )

This is the main building block of our dsl language. Now we could start to define our domain.

type Id = int type Entity < ' e > = Entity of Id * ' e [< Measure >] type money type User = { name : string ; email : string ; balance : int < money >} type Product = { name : string ; quantity : int ; price : int < money >} type Email = { body : string ; subject : string }

Database operations is a good way to represent dsls composition. So we have for example one language for our problem domain and one as an sub dsl for database ops(Something like DDD’s repository pattern). Usually it is not the best way to do things but good enough for our example.

type DbOps < ' e , ' k > = | Select of Request < unit , Entity < ' e > seq , ' k > | Get of Request < Id , Entity < ' e > option , ' k > | Delete of Request < Entity < ' e >, unit , ' k > | Update of Request < Entity < ' e >, unit , ' k > | Insert of Request < ' e , Id , ' k > let bindDb v f bind = match v with | Select ( r ) -> Select ( bindRequest bind f r ) | Get ( r ) -> Get ( bindRequest bind f r ) | Delete ( r ) -> Delete ( bindRequest bind f r ) | Update ( r ) -> Update ( bindRequest bind f r ) | Insert ( r ) -> Insert ( bindRequest bind f r )

As you could see databse dsl in bind uses bindRequest function and additional bind function of parent dsl. Lets finally describe our main dsl.

type Dsl < ' r > = | UsersTable of DbOps < User , Dsl < ' r >> | ProductsTable of DbOps < Product , Dsl < ' r >> | SendEmail of Request < User * Email , unit , Dsl < ' r >> | Log of Request < string , unit , Dsl < ' r >> | Download of Request < string , string , Dsl < ' r >> | Pure of ' r type DslBuilder () = member x . Bind ( v : Dsl < ' a >, f : ' a -> Dsl < ' b >) = match v with | UsersTable ( dbOp ) -> UsersTable ( bindDb dbOp f x . Bind ) | ProductsTable ( dbOp ) -> ProductsTable ( bindDb dbOp f x . Bind ) | SendEmail ( r ) -> SendEmail ( bindRequest x . Bind f r ) | Log ( r ) -> Log ( bindRequest x . Bind f r ) | Download ( r ) -> Download ( bindRequest x . Bind f r ) | Pure ( v ) -> f ( v ) member x . Return v = Pure ( v ) member x . ReturnFrom v = v let dsl = DslBuilder ()

So as you can see it is just a boilerplate code which probably could be generated by a type provider for you. Now we need to lift our type constructors into our dsl monad.

let lift ctor i = ctor ( i , fun s -> Pure ( s )) let usersTable op = lift ( UsersTable << op ) let productsTable op = lift ( ProductsTable << op ) let sendEmail = lift SendEmail let log = lift Log let download = lift Download

Now we can write programs by using lifted funcs in dsl builder. But before that lest create a fake interpreter.

type Db = { users : Map < Id , User > products : Map < Id , Product > } let runDb ( table : Map <_,_>) dbOp = match dbOp with | Select (_, k ) -> table |> Seq . map ( fun kv -> Entity ( kv . Key , kv . Value )) |> k , table | Get ( id , k ) -> if table . ContainsKey id then k ( Some ( Entity ( id , table .[ id ]))), table else k None , table | Delete ( Entity ( id ,_), k ) -> k () , table . Remove id | Update ( Entity ( id , v ), k ) -> k () , table |> Map . remove id |> Map . add id v | Insert ( v , k ) -> let id = table |> Seq . map ( fun kv -> kv . Key ) |> Seq . max k id , Map . add ( id + 1 ) v table open System . Net open System . Text open System let rec run db ast = async { match ast with | ProductsTable ( dbOp ) -> let r , t = runDb db . products dbOp return ! run { db with products = t } r | UsersTable ( dbOp ) -> let r , t = runDb db . users dbOp return ! run { db with users = t } r | SendEmail (( u , e ), k ) -> printfn "Sending email to: %s

subject:%s

body:%s" u . name e . subject e . body return ! k () |> run db | Log ( r , k ) -> printfn "Log(%A):%s" ( System . DateTime . Now ) r return ! k () |> run db | Download ( r , k ) -> let client = new WebClient () client . Encoding <- Encoding . GetEncoding ( "utf-8" ) let ! html = client . AsyncDownloadString ( new Uri ( r )) return ! k ( html ) |> run db | Pure ( v ) -> return v , db }

As you can see our abstract download function has no effects because all effects exist only in interpreter. In our case download has async effect.

So everything is ready for programming.

let optZip a b = match a , b with | Some ( a ), Some ( b ) -> Some ( a , b ) | _ -> None let transferProductToUser p u count = if p . quantity < count then Choice2Of2 ( sprintf "no enough quantity product '%s' quantity %d requested %d" p . name p . quantity count ) elif u . balance < p . price * count then Choice2Of2 ( sprintf "no enough money product '%s' user balance %d requested sum %d" p . name u . balance ( p . quantity * p . price )) else let p = { p with quantity = p . quantity - count } let u = { u with balance = u . balance - p . price * count } Choice1Of2 ( p , u ) let getAndLog tname table id = dsl { let ! p = table Get id match p with | Some (_) -> return p | None -> do ! log <| sprintf "unable to find %d in %s" id tname return None } let buyProduct pid uid count = dsl { let ! p = getAndLog "products" productsTable pid let ! u = getAndLog "users" usersTable uid match optZip u p with | Some ( Entity ( idu , u ), Entity ( idp , p )) -> do ! log ( "found product and user" ) let res = transferProductToUser p u count match res with | Choice1Of2 ( p , u ) -> do ! sendEmail ( u , { body = "you bought a product" ; subject = sprintf "success bought %s quantity %d" p . name count }) do ! productsTable Update ( Entity ( idp , p )) do ! usersTable Update ( Entity ( idu , u )) return true | Choice2Of2 ( error ) -> do ! log ( error ) return false | None -> return false } let program quantity = dsl { let ! isOK = buyProduct 1 1 quantity if isOK then let ! html = download "http://google.com" return "ok " + html . Substring ( 0 , 100 ) else return "not ok" } let db = { users = [ 1 , { name = "hodza" ; email = "email@mail.com" ; balance = 100 < money >}] |> Map . ofList products = [ 1 , { name = "Fsharp fun and drugs" ; quantity = 10 ; price = 1 < money >}] |> Map . ofList }

lets run our abstract program with fake interpreter.

printfn "run interpret" printfn "before %A" db run db ( program 9 ) |> Async . RunSynchronously |> printfn "result quantity 9 %A" run db ( program 21 ) |> Async . RunSynchronously |> printfn "result quantity 21 %A"

and the result is

//run interpret //before {users = map [(1, {name = "hodza"; // email = "email@mail.com"; // balance = 100;})]; // products = map [(1, {name = "Fsharp fun and drugs"; // quantity = 10; // price = 1;})];} //Log(11.02.2016 18:21:36):found product and user //Sending email to: hodza //subject:success bought Fsharp fun and drugs quantity 9 //body:you bought a product //result quantity 9 ("ok <!doctype html> <html itemscope="" itemtype="http://schema.org/WebPage" lang="ru"> <head><meta content", // {users = map [(1, {name = "hodza"; // email = "email@mail.com"; // balance = 91;})]; // products = map [(1, {name = "Fsharp fun and drugs"; // quantity = 1; // price = 1;})];}) // =============================================================== //Log(11.02.2016 18:21:36):found product and user //Log(11.02.2016 18:21:36):no enough quantity product 'Fsharp fun and drugs' quantity 10 requested 21 //result quantity 21 ("not ok", {users = map [(1, {name = "hodza"; // email = "email@mail.com"; // balance = 100;})]; // products = map [(1, {name = "Fsharp fun and drugs"; // quantity = 10; // price = 1;})];})

Code here

We used an fake ad hoc interpreter in this post, but we could describe interpreter as a data structure(comonad). It allows us to abstract and compose interpreters. More advanced version with comonadic interpreter here

Result

Now we can write abstract programs which are easy to test with fake interpreters and we abstract our code from execution effects. No more code rewrite when we decided to use async/lazy version of some method.

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