I am doing a project and I find myself standing in the following situation:
I am creating a Long-Short portfolio in which I currently have daily returns. My next step would be to calculate the cumulative returns, but I am having trouble trying to do so.
Could anyone help with how to do it?
Thanks in advance.
The code
let long = myFactorPorts.Rows |> Seq.filter(fun row -> row.PortfolioName = "Mine" && row.Index = Some 3)
let short = myFactorPorts.Rows |> Seq.filter(fun row -> row.PortfolioName = "Mine" && row.Index = Some 1)
type Return = { YearMonth : DateTime; Return : float }
let longShort =
let shortMap = short |> Seq.map(fun row -> row.YearMonth, row) |> Map
long
|> Seq.map(fun longObs ->
match Map.tryFind longObs.YearMonth shortMap with
| None -> failwith "probably your date variables are not aligned"
| Some shortObs -> { YearMonth = longObs.YearMonth; Return = longObs.Ret - shortObs.Ret })
|> Seq.toArray
longShort |> Array.take 3
let cumulativereturnslongshort = longShort |> ??
Your question is a bit unclear, because you show us some code related to how you get the data, but you do not say too much about what you want to do and where you are stuck.
However, if I understand it, you have an array of Return values. I'll use a simple example:
type Return = { YearMonth : DateTime; Return : float }
let longShort =
[| { YearMonth = DateTime(2021,1,1); Return = 1.0 }
{ YearMonth = DateTime(2021,2,1); Return = -3.0 }
{ YearMonth = DateTime(2021,3,1); Return = 5.0 }
{ YearMonth = DateTime(2021,4,1); Return = -1.0 } |]
You say you want to understand cummulative returns. I guess this means just summing the previous returns, so the cummulative returns based on the above monthly returns would be 1, -2, 3, 2. If that's the case, you can use Array.scan:
longShort
|> Array.scan (fun prev item ->
{ item with Return = item.Return + prev.Return})
{ YearMonth = DateTime.MinValue; Return = 0.0 }
|> Array.skip 1
The scan function lets you calculate new value for each item in the array, using some state that is passed along. Here, I use the previous Return value as the state (and the function passed to scan just adds the current to the previous return). One trick is that you need some initial value, so I create a Return value with Return = 0.0, but then skip over this to get the result.
Related
Can someone tell me how I can update a subitem in a nested record?
I want to set isSelected to true for the Item with value = "B"
type MyItem = {isSelected:bool; value:string}
type MyModel = {list:MyItem list}
let a = {isSelected = false; value = "A"}
let b = {isSelected = false; value = "B"}
let c = {isSelected = false; value = "C"}
let m = {list = [a;b;c]}
let m2 = { m with list = { m.list with ??? = { ??? }}}
I will not use mutable data structures.
Immutability is great but when dealing with nested immutable structures it can get a bit hairy. Especially if it's deeply nested.
One way to deal with this is so called Lenses.
So I increased the nesting level of the example a bit so that the value of lenses are more visible.
module Lenses =
// This lens is a pair of function, a getter that get's inner value of an object
// and a setter that sets the inner value of an object
// The cool thing is that a lens is composable meaning we can create a lens
// that allows us to get and set a deeply nested property succinctly
type Lens<'O, 'I> = L of ('O -> 'I)*('I -> 'O -> 'O)
let lens (g : 'O -> 'I) (s : 'I -> 'O -> 'O) = L (g, s)
// Gets an inner value
let get (L (g, _)) o = g o
// Sets an inner value
let set (L (_, s)) i o = s i o
// Updates an inner value given an updater function that sees the
// inner value and returns a new value
let over (L (g, s)) u o = s (u (g o)) o
// Compose two lenses into one, allows for navigation into deeply nested structures
let compose (L (og, os)) (L (ig, is)) =
let g o = ig (og o)
let s i o = os (is i (og o)) o
L (g, s)
type Lens<'O, 'I> with
static member (-->) (o, i) = compose o i
open Lenses
// I made the model a bit more complex to show benefit of lenses
type MySelection =
{
isSelected: bool
}
// Define a lens that updates the property, this code can potentially be generated
// Scala does this with macros, in F# there are other possibilities
static member isSelectedL : Lens<MySelection, bool> = lens (fun o -> o.isSelected) (fun i o -> { o with isSelected = i })
type MyValue =
{
value: string
}
static member valueL : Lens<MyValue, string> = lens (fun o -> o.value) (fun i o -> { o with value = i })
type MyItem =
{
selection : MySelection
value : MyValue
}
static member selectionL : Lens<MyItem, MySelection> = lens (fun o -> o.selection) (fun i o -> { o with selection = i })
static member valueL : Lens<MyItem, MyValue> = lens (fun o -> o.value ) (fun i o -> { o with value = i })
type MyModel =
{
list: MyItem list
}
static member listL : Lens<MyModel, MyItem list> = lens (fun o -> o.list) (fun i o -> { o with list = i })
[<EntryPoint>]
let main argv =
// Define example model
let a = {selection = {isSelected = false}; value = {value = "A"}}
let b = {selection = {isSelected = false}; value = {value = "B"}}
let c = {selection = {isSelected = false}; value = {value = "C"}}
let m = {list = [a;b;c]}
// Print it
printfn "%A" m
// Update the model
let m2 =
let mapper (v : MyItem) =
// Grabs the nest value using lens composition
let nestedValue = v |> get (MyItem.valueL --> MyValue.valueL)
let isSelected = nestedValue = "B"
// Set the nested isSelected using lens composition
v |> set (MyItem.selectionL --> MySelection.isSelectedL) isSelected
// Maps nested list property
m |> over MyModel.listL (List.map mapper)
printfn "%A" m2
0
Use List.map:
let m2 =
{ m with list =
List.map (fun item ->
if item.value = "B" then
{ item with isSelected = true }
else
item)
m.list
}
This will create a new list where every item is the same as before, except the one we want to "update" because we replace that with a new item where isSelected is true.
I am writing a raytracer in F# and I am trying to use multithreading in the montecarlo sampling step.
However, when I run my code with the async variant, the program never returns and runs indefinitely.
My Code Currently:
let rec rayTrace previousTraceDepth ((ray : Ray) , (accEmitted : Color) , (accScatter :Color)) =
if previousTraceDepth > maxTraceDepth
then
accEmitted + backgroundColor*accScatter
else
let newTraceDepth = previousTraceDepth + 1us
let (realSolution,t,surface) = findClosestIntersection ray surfaces
let surfaceGeometry : Hitable = surface.Geometry
if surfaceGeometry.IntersectionAcceptable realSolution t 1.0f (PointForRay ray t)
then
let emittedShading = surface.Emitted
let e = accEmitted + accScatter*emittedShading
let mcSamples = surface.SampleCount
//Synchronous
// let mutable totalShading = e/surface.MCNormalization
// for _ in 1..mcSamples do
// let (doesRayContribute,outRay,cosOfIncidence) = surface.Scatter ray t ((int)newTraceDepth)
// let shading = surface.BRDF*cosOfIncidence / (surface.PDF*surface.MCNormalization)
// let s = accScatter*shading
// totalShading <- totalShading + (rayTrace newTraceDepth (outRay , e , s))
// totalShading
let eMCAdjusted = e / surface.MCNormalization
let shadingSamplesAsync =
[|
for _ in 1..mcSamples -> async {
let (doesRayContribute,outRay,cosOfIncidence) = surface.Scatter ray t ((int)newTraceDepth)
let shading = surface.BRDF*cosOfIncidence / (surface.PDF*surface.MCNormalization)
let s = accScatter*shading
return rayTrace newTraceDepth (outRay,e,s)
}|]
if Array.isEmpty shadingSamplesAsync then
e
else
let shadingSamplesSync = shadingSamplesAsync |> Async.Parallel |> Async.RunSynchronously
Array.sumBy (fun x -> eMCAdjusted + x) shadingSamplesSync
else
accEmitted + backgroundColor*accScatter
How can I make this method async recursive?
I found the cause of the problem:
I was actually calling Async.RunSynchronously from the entry point method i.e rayTraceBase. Apparently nested Async.RunSynchronously is not a good thing. After I removed the second Async.RunSynchronously the code worked.
But it is painfully slow since async contexts are created all over the place and the GC runs non stop.
I want to sort items of a class and collect them in Collection-Classes that beside a List-Member also contain further information that are necessary for the sorting process.
The following example is a a very simplified example for my problem. Although it doesn't make sense, I hope it still can help to understand my Question.
type ItemType = Odd|Even //realworld: more than two types possible
type Item(number) =
member this.number = number
member this.Type = if (this.number % 2) = 0 then Even else Odd
type NumberTypeCollection(numberType:ItemType , ?items:List<Item>) =
member this.ItemType = numberType
member val items:List<Item> = defaultArg items List.empty<Item> with get,set
member this.append(item:Item) = this.items <- item::this.items
let addToCollection (collections:List<NumberTypeCollection>) (item:Item) =
let possibleItem =
collections
|> Seq.where (fun c -> c.ItemType = item.Type) //in my realworld code, several groups may be returned
|> Seq.tryFind(fun _ -> true)
match possibleItem with
|Some(f) -> f.append item
collections
|None -> NumberTypeCollection(item.Type, [item]) :: collections
let rec findTypes (collections:List<NumberTypeCollection>) (items:List<Item>) =
match items with
| [] -> collections
| h::t -> let newCollections = ( h|> addToCollection collections)
findTypes newCollections t
let items = [Item(1);Item(2);Item(3);Item(4)]
let finalCollections = findTypes List.empty<NumberTypeCollection> items
I'm unsatisfied with the addToCollection method, since it requires the items in NumberTypeCollection to be mutual. Maybe there are further issues.
What can be a proper functional solution to solve this issue?
Edit: I'm sorry. May code was too simplified. Here is a little more complex example that should hopefully illustrate why I chose the mutual class-member (although this could still be the wrong decision):
open System
type Origin = Afrika|Asia|Australia|Europa|NorthAmerika|SouthAmerica
type Person(income, taxrate, origin:Origin) =
member this.income = income
member this.taxrate = taxrate
member this.origin = origin
type PersonGroup(origin:Origin , ?persons:List<Person>) =
member this.origin = origin
member val persons:List<Person> = defaultArg persons List.empty<Person> with get,set
member this.append(person:Person) = this.persons <- person::this.persons
//just some calculations to group people into some subgroups
let isInGroup (person:Person) (personGroup:PersonGroup) =
let avgIncome =
personGroup.persons
|> Seq.map (fun p -> float(p.income * p.taxrate) / 100.0)
|> Seq.average
Math.Abs ( (avgIncome / float person.income) - 1.0 ) < 0.5
let addToGroup (personGroups:List<PersonGroup>) (person:Person) =
let possibleItem =
personGroups
|> Seq.where (fun p -> p.origin = person.origin)
|> Seq.where (isInGroup person)
|> Seq.tryFind(fun _ -> true)
match possibleItem with
|Some(f) -> f.append person
personGroups
|None -> PersonGroup(person.origin, [person]) :: personGroups
let rec findPersonGroups (persons:List<Person>) (personGroups:List<PersonGroup>) =
match persons with
| [] -> personGroups
| h::t -> let newGroup = ( h|> addToGroup personGroups)
findPersonGroups t newGroup
let persons = [Person(1000,20, Afrika);Person(1300,22,Afrika);Person(500,21,Afrika);Person(400,20,Afrika)]
let c = findPersonGroups persons List.empty<PersonGroup>
What I may need to emphasize: There can be several different groups with the same origin.
Tomas' solution using groupby is the optimal approach if you want to generate your collections only once, it's a simple and concise.
If you want to be able to add/remove items in a functional, referentially transparent style for this type of problem, I suggest you move away from seq and start using Map.
You have a setup which is fundamentally dictionary-like. You have a unique key and a value. The functional F# equivalent to a dictionary is a Map, it is an immutable data structure based on an AVL tree. You can insert, remove and search in O(log n) time. When you append/remove from the Map, the old Map is maintained and you receive a new Map.
Here is your code expressed in this style
type ItemType =
|Odd
|Even
type Item (number) =
member this.Number = number
member this.Type = if (this.Number % 2) = 0 then Even else Odd
type NumTypeCollection = {Items : Map<ItemType, Item list>}
/// Functions on NumTypeCollection
module NumberTypeCollection =
/// Create empty collection
let empty = {Items = Map.empty}
/// Append one item to the collection
let append (item : Item) numTypeCollection =
let key = item.Type
match Map.containsKey key numTypeCollection.Items with
|true ->
let value = numTypeCollection.Items |> Map.find key
let newItems =
numTypeCollection.Items
|> Map.remove key
|> Map.add key (item :: value) // append item
{Items = newItems }
|false -> {Items = numTypeCollection.Items |> Map.add key [item]}
/// Append a list of items to the collections
let appendList (item : Item list) numTypeCollection =
item |> List.fold (fun acc it -> append it acc) numTypeCollection
Then call it using:
let items = [Item(1);Item(2);Item(3);Item(4)]
let finalCollections = NumberTypeCollection.appendList items (NumberTypeCollection.empty)
If I understand your problem correctly, you're trying to group the items by their type. The easiest way to do that is to use the standard library function Seq.groupBy. The following should implement the same logic as your code:
items
|> Seq.groupBy (fun item -> item.Type)
|> Seq.map (fun (key, values) ->
NumberTypeCollection(key, List.ofSeq values))
Maybe there are further issues.
Probably. It's difficult to tell, since it's hard to detect the purpose of the OP code... still:
Why do you even need an Item class? Instead, you could simply have a itemType function:
let itemType i = if i % 2 = 0 then Even else Odd
This function is referentially transparent, which means that you can replace it with its value if you wish. That makes it as good as a property getter method, but now you've already saved yourself from introducing a new type.
Why define a NumberTypeCollection class? Why not a simple record?
type NumberTypeList = { ItemType : ItemType; Numbers : int list }
You can implement addToCollection like something like this:
let addToCollection collections i =
let candidate =
collections
|> Seq.filter (fun c -> c.ItemType = (itemType i))
|> Seq.tryHead
match candidate with
| Some x ->
let x' = { x with Numbers = i :: x.Numbers }
collections |> Seq.filter ((<>) x) |> Seq.append [x']
| None ->
collections |> Seq.append [{ ItemType = (itemType i); Numbers = [i] }]
Being immutable, it doesn't mutate the input collections, but instead returns a new sequence of NumberTypeList.
Also notice the use of Seq.tryHead instead of Seq.tryFind(fun _ -> true).
Still, if you're attempting to group items, then Tomas' suggestion of using Seq.groupBy is more appropriate.
I am not sure about "exclusive state management" thing in the title, I did my best making it up trying to put the problem concisely.
I am porting some of my C# code to F# trying to do it as idiomatic as I can. I have an entity that requests a number of ID's from a sequence in my database and then dispenses these ID to anyone in need. Once an id is given out it should no longer be available for anybody else. Hence there must be some sort of state associated with that entity that keeps track of the remaining number of IDs. Since using a mutable state is not idiomatic, what I can do is to write something like this:
let createIdManager =
let idToStartWith = 127
let allowed = 10
let givenOut = 0
(idToStartWith, allowed, givenOut)
-
let getNextAvailableId (idToStartWith, allowed, givenOut) =
if givenOut< allowed
then ((idToStartWith, allowed, givenOut+ 1), Some(idToStartWith + givenOut))
else ((idToStartWith, allowed, givenOut), None)
let (idManager, idOpt) = getNextAvailableId createIdManager()
match idOpt with
| Some(id) -> printf "Yay!"
| None -> reloadIdManager idManager |> getNextAvailableId
This approach is idiomatic (as far as I can tell) but extremely vulnerable. There are so many ways to get it messed up. My biggest concern is that once an id is advanced and a newer copy of id manager is made, there is no force that can stop you from using the older copy and get the same id again.
So how do I do exclusive state management, per se, in F#?
If you only need to initialize the set of ids once then you can simply hide a mutable reference to a list inside a local function scope, as in:
let nextId =
let idsRef = ref <| loadIdsFromDatabase()
fun () ->
match idsRef.Value with
| [] ->
None
| id::ids ->
idsRef := ids
Some id
let id1 = nextId ()
let id2 = nextId ()
You could use a state-monad(Computational Expression).
First we declare the state-monad
type State<'s,'a> = State of ('s -> 'a * 's)
type StateBuilder<'s>() =
member x.Return v : State<'s,_> = State(fun s -> v,s)
member x.Bind(State v, f) : State<'s,_> =
State(fun s ->
let (a,s) = v s
let (State v') = f a
v' s)
let withState<'s> = StateBuilder<'s>()
let runState (State f) init = f init
Then we define your 'IdManager' and a function to get the next available id as well as the new state after the execution of the function.
type IdManager = {
IdToStartWith : int
Allowed : int
GivenOut : int
}
let getNextId state =
if state.Allowed > state.GivenOut then
Some (state.IdToStartWith + state.GivenOut), { state with GivenOut = state.GivenOut + 1 }
else
None, state
Finally we define our logic that requests the ids and execute the state-monad.
let idStateProcess =
withState {
let! id1 = State(getNextId)
printfn "Got id %A" id1
let! id2 = State(getNextId)
printfn "Got id %A" id2
//...
return ()
}
let initState = { IdToStartWith = 127; Allowed = 10; GivenOut = 0 }
let (_, postState) =
runState
idStateProcess
initState //This should be loaded from database in your case
Output:
Got id Some 127
Got id Some 128
I want to update a nested, immutable data structure (I attached a small example of a hypothetical game.) And I wonder whether this can be done a little more elegantly.
Every time something inside the dungeon changes we need a new dungeon. So, I gave it a general update member. The best way to use this, that I could come up with for the general case, is to specify the processing functions for each nesting and than pass the combined function to the update member.
Then, for really common cases (like applying a map to all the monsters on a specific level), I provide extra members (Dungeon.MapMonstersOnLevel).
The whole thing works, I would just like to know, if anyone can think of better ways of doing it.
Thanks!
// types
type Monster(awake : bool) =
member this.Awake = awake
type Room(locked : bool, monsters : Monster list) =
member this.Locked = locked
member this.Monsters = monsters
type Level(illumination : int, rooms : Room list) =
member this.Illumination = illumination
member this.Rooms = rooms
type Dungeon(levels : Level list) =
member this.Levels = levels
member this.Update levelFunc =
new Dungeon(this.Levels |> levelFunc)
member this.MapMonstersOnLevel (f : Monster -> Monster) nLevel =
let monsterFunc = List.map f
let roomFunc = List.map (fun (room : Room) -> new Room(room.Locked, room.Monsters |> monsterFunc))
let levelFunc = List.mapi (fun i (level : Level) -> if i = nLevel then new Level(level.Illumination, level.Rooms |> roomFunc) else level)
new Dungeon(this.Levels |> levelFunc)
member this.Print() =
this.Levels
|> List.iteri (fun i e ->
printfn "Level %d: Illumination %d" i e.Illumination
e.Rooms |> List.iteri (fun i e ->
let state = if e.Locked then "locked" else "unlocked"
printfn " Room %d is %s" i state
e.Monsters |> List.iteri (fun i e ->
let state = if e.Awake then "awake" else "asleep"
printfn " Monster %d is %s" i state)))
// generate test dungeon
let m1 = new Monster(true)
let m2 = new Monster(false)
let m3 = new Monster(true)
let m4 = new Monster(false)
let m5 = new Monster(true)
let m6 = new Monster(false)
let m7 = new Monster(true)
let m8 = new Monster(false)
let r1 = new Room(true, [ m1; m2 ])
let r2 = new Room(false, [ m3; m4 ])
let r3 = new Room(true, [ m5; m6 ])
let r4 = new Room(false, [ m7; m8 ])
let l1 = new Level(100, [ r1; r2 ])
let l2 = new Level(50, [ r3; r4 ])
let dungeon = new Dungeon([ l1; l2 ])
dungeon.Print()
// toggle wake status of all monsters
let dungeon1 = dungeon.MapMonstersOnLevel (fun m -> new Monster(not m.Awake)) 0
dungeon1.Print()
// remove monsters that are asleep which are in locked rooms on levels where illumination < 100 and unlock those rooms
let monsterFunc2 = List.filter (fun (monster : Monster) -> monster.Awake)
let roomFunc2 = List.map(fun (room : Room) -> if room.Locked then new Room(false, room.Monsters |> monsterFunc2) else room)
let levelFunc2 = List.map(fun (level : Level) -> if level.Illumination < 100 then new Level(level.Illumination, level.Rooms |> roomFunc2) else level)
let dungeon2 = dungeon.Update levelFunc2
dungeon2.Print()
Here's the same code using lenses as currently defined in FSharpx.
As other answers note, it's convenient to use records here; they give you structural equality for free among other things.
I also attach the corresponding lenses for the properties as static members; you can also define them in a module or as loose functions. I prefer static members here, for practical purposes it's just like a module.
open FSharpx
type Monster = {
Awake: bool
} with
static member awake =
{ Get = fun (x: Monster) -> x.Awake
Set = fun v (x: Monster) -> { x with Awake = v } }
type Room = {
Locked: bool
Monsters: Monster list
} with
static member locked =
{ Get = fun (x: Room) -> x.Locked
Set = fun v (x: Room) -> { x with Locked = v } }
static member monsters =
{ Get = fun (x: Room) -> x.Monsters
Set = fun v (x: Room) -> { x with Monsters = v } }
type Level = {
Illumination: int
Rooms: Room list
} with
static member illumination =
{ Get = fun (x: Level) -> x.Illumination
Set = fun v (x: Level) -> { x with Illumination = v } }
static member rooms =
{ Get = fun (x: Level) -> x.Rooms
Set = fun v (x: Level) -> { x with Rooms = v } }
type Dungeon = {
Levels: Level list
} with
static member levels =
{ Get = fun (x: Dungeon) -> x.Levels
Set = fun v (x: Dungeon) -> { x with Levels = v } }
static member print (d: Dungeon) =
d.Levels
|> List.iteri (fun i e ->
printfn "Level %d: Illumination %d" i e.Illumination
e.Rooms |> List.iteri (fun i e ->
let state = if e.Locked then "locked" else "unlocked"
printfn " Room %d is %s" i state
e.Monsters |> List.iteri (fun i e ->
let state = if e.Awake then "awake" else "asleep"
printfn " Monster %d is %s" i state)))
I also define print as a static member; again it's like a function in a module, and it's more composable than an instance method (though I won't compose it here).
Now to generate the sample data. I think { Monster.Awake = true } is more desciptive than new Monster(true). If you wanted to use classes I'd name the parameter explicitly, e.g. Monster(awake: true)
// generate test dungeon
let m1 = { Monster.Awake = true }
let m2 = { Monster.Awake = false }
let m3 = { Monster.Awake = true }
let m4 = { Monster.Awake = false }
let m5 = { Monster.Awake = true }
let m6 = { Monster.Awake = false }
let m7 = { Monster.Awake = true }
let m8 = { Monster.Awake = false }
let r1 = { Room.Locked = true; Monsters = [m1; m2] }
let r2 = { Room.Locked = false; Monsters = [m3; m4] }
let r3 = { Room.Locked = true; Monsters = [m5; m6] }
let r4 = { Room.Locked = false; Monsters = [m7; m8] }
let l1 = { Level.Illumination = 100; Rooms = [r1; r2] }
let l2 = { Level.Illumination = 50; Rooms = [r3; r4] }
let dungeon = { Dungeon.Levels = [l1; l2] }
Dungeon.print dungeon
Now comes the fun part: composing lenses to update the monsters for all rooms for a particular level in a dungeon:
open FSharpx.Lens.Operators
let mapMonstersOnLevel nLevel f =
Dungeon.levels >>| Lens.forList nLevel >>| Level.rooms >>| Lens.listMap Room.monsters
|> Lens.update (f |> List.map |> List.map)
// toggle wake status of all monsters
let dungeon1 = dungeon |> mapMonstersOnLevel 0 (Monster.awake.Update not)
Dungeon.print dungeon1
For the second dungeon I also use lenses but without lens composition. It's sort of a DSL defined by small composed functions (some of the functions are from lenses). Maybe there are lenses to express this more concisely, but I haven't figured it out.
// remove monsters that are asleep
// which are in locked rooms on levels where illumination < 100
// and unlock those rooms
let unlock = Room.locked.Set false
let removeAsleepMonsters = Room.monsters.Update (List.filter Monster.awake.Get)
let removeAsleepMonsters_unlock_rooms = List.mapIf Room.locked.Get (unlock >> removeAsleepMonsters)
let isLowIllumination = Level.illumination.Get >> ((>)100)
let removeAsleepMonsters_unlock_level = Level.rooms.Update removeAsleepMonsters_unlock_rooms
let removeAsleepMonsters_unlock_levels = List.mapIf isLowIllumination removeAsleepMonsters_unlock_level
let dungeon2 = dungeon |> Dungeon.levels.Update removeAsleepMonsters_unlock_levels
Dungeon.print dungeon2
I overused lenses and pointfree a bit here, partially on purpose, just to show what it could look like. Some won't like it, claiming it's not idiomatic or clear. Maybe so, but it's another tool that you can choose to use or not, depending on your context.
But more importantly, because Update is a Get followed by a function followed by a Set, this isn't as efficient as your code when it comes to processing lists: an Update in Lens.forList first gets the nth element in the list, which is an O(n) operation.
To summarize:
Pros:
Very concise.
Enables pointfree style.
Code involving lenses is generally oblivious of the source type representation (it can be a class, a record, a single-case DU, a dictionary, it doesn't matter).
Cons:
May be inefficient for some cases in current implementation.
Due to lack of macros, requires some boilerplate.
Thanks for this example, as a result I'll be revising the current design of lenses in FSharpx and see if it can be optimized.
I committed this code to the FSharpx repository: https://github.com/fsharp/fsharpx/commit/136c763e3529abbf91ad52b8127ce11cbb3dff28
I asked a similar question, but about haskell: Is there a Haskell idiom for updating a nested data structure?
The excellent answers mentioned a concept known as functional lenses.
Unfortunately, I don't know what the package is, or if it even exists, for F#.
Update: two knowledgeable F#-ists (F#-ers? F#as?) left useful links about this in comments, so I'll post them here:
#TomasPetricek suggested FSharpX and this website describing it
#RyanRiley gave the link for the package
It's awesome that these two guys took the time to read my answer, comment and improve it, as they're both developers of FSharpX!
More extraneous information: I was motivated to figure out how to do this by Clojure's assoc-in and update-in functions, which proved to me that it is possible in functional languages! Of course, Clojure's dynamic typing makes it simpler than in Haskell/F#. Haskell's solution involves templating, I believe.
I posted a similar question about Scala about a year back. The answers mention three concepts as a solution to this problem: Zippers, Tree rewriting, and Lenses.
I don't know why you want to use classes here. I think you can leverage the power of pattern matching if you use records for holding data and keeping them minimal:
// Types
type Monster = {
Awake: bool
}
with override x.ToString() =
if x.Awake then "awake" else "asleep"
type Room = {
Locked: bool;
Monsters: Monster list
}
with override x.ToString() =
let state = if x.Locked then "locked" else "unlocked"
state + "\n" + (x.Monsters |> List.mapi (fun i m -> sprintf " Monster %d is %s" i (string m)) |> String.concat "\n")
type Level = {
Illumination : int;
Rooms : Room list
}
with override x.ToString() =
(string x.Illumination) + "\n" + (x.Rooms |> List.mapi (fun i r -> sprintf " Room %d is %s" i (string r)) |> String.concat "\n")
type Dungeon = {
Levels: Level list;
}
with override x.ToString() =
x.Levels |> List.mapi (fun i l -> sprintf "Level %d: Illumination %s" i (string l)) |> String.concat "\n"
To me, putting functions for manipulating Dungeon inside the class is unnatural. The code looks better if you put them in a module and make use of above declarations:
/// Utility functions
let updateMonster (m: Monster) a =
{m with Awake = a}
let updateRoom (r: Room) l monstersFunc =
{ Locked = l;
Monsters = r.Monsters |> monstersFunc}
let updateLevel (l: Level) il roomsFunc =
{Illumination = il; Rooms = l.Rooms |> roomsFunc}
let updateDungeon (d: Dungeon) levelsFunc =
{d with Levels = d.Levels |> levelsFunc}
/// Update functions
let mapMonstersOnLevel (d: Dungeon) nLevel =
let monstersFunc = List.map (fun m -> updateMonster m (not m.Awake))
let roomsFunc = List.map (fun r -> updateRoom r r.Locked monstersFunc)
let levelsFunc = List.mapi (fun i l -> if i = nLevel then updateLevel l l.Illumination roomsFunc else l)
updateDungeon d levelsFunc
let removeSleptMonsters (d: Dungeon) =
let monstersFunc = List.filter (fun m -> m.Awake)
let roomsFunc = List.map (fun r -> if r.Locked then updateRoom r false monstersFunc else r)
let levelsFunc = List.map (fun l -> if l.Illumination < 100 then updateLevel l l.Illumination roomsFunc else l)
updateDungeon d levelsFunc
Then you can see manipulating these nested data structures is much easier. However, above functions still have redundancy. You can refactor more if you use lenses which come very natural with records. Check out the insightful article by Mauricio Scheffer, which is really close to this formulation.
I've implemented a lens library in C# via reflection. The core of the library is
this function
/// <summary>
/// Perform an immutable persistent set on a sub
/// property of the object. The object is not
/// mutated rather a copy of the object with
/// the required change is returned.
/// </summary>
/// <typeparam name="ConvertedTo">type of the target object</typeparam>
/// <typeparam name="V">type of the value to be set</typeparam>
/// <param name="This">the target object</param>
/// <param name="names">the list of property names composing the property path</param>
/// <param name="value">the value to assign to the property</param>
/// <returns>A new object with the required change implemented</returns>
private static T Set<T, V>
(this T This, List<string> names, V value)
where T : class, Immutable
{
var name = names.First();
var rest = names.Skip(1).ToList();
if (names.Count == 1)
{
var copy = This.ShallowClone();
copy.SetPrivatePropertyValue(names.First(), value);
return copy as T;
}
else
{
var copy = This.ShallowClone();
var subtree = copy
.GetPrivatePropertyValue<Immutable>(name)
.Set(rest, value);
copy.SetPrivatePropertyValue(names.First(), subtree);
return copy as T;
}
}
The above function is composed using helper library into various utilities,
one of which is an undo stack based on immutable persistent records. There
is an overload of this function
public static Maybe<T> MaybeSet<T,V>
(this T This, Expression<Func<T, V>> prop, V value)
where T : class, Immutable
{
if (!EqualityComparer<V>.Default.Equals(This.Get(prop.Compile()),value))
{
var names = ReactiveUI.Reflection.ExpressionToPropertyNames(prop).ToList();
return This.Set(names, value).ToMaybe();
}
else
{
return None<T>.Default;
}
}
which allows more natural type safe notation using LINQ expressions.
foo = foo.Set(f=>f.A.B.C, 10);
There is a lot of reflection going on in the library but the reduction
in boilerplate is worth the performance hit. See the spec. I only need to
tag the record as Immutable to get it to work. I don't have to
provide getters and settors.
class A : Immutable
{
public int P { get; private set; }
public B B { get; private set; }
public A(int p, B b)
{
P = p;
B = b;
}
}
class B : Immutable
{
public int P { get; private set; }
public C C { get; private set; }
public B(int p, C c)
{
P = p;
C = c;
}
}
class C : Immutable
{
public int P { get; private set; }
public C(int p)
{
P = p;
}
}
namespace Utils.Spec
{
public class ImmutableObjectPatternSpec : IEnableLogger
{
[Fact]
public void SetterSpec()
{
var a = new A
( p:10
, b: new B
( p: 20
, c : new C(30)));
var a_ = a.Set(p => p.B.C.P, 10);
a.Should().NotBe(a_);
a.B.C.P.Should().Be(30);
a_.B.C.P.Should().Be(10);
}
[Fact]
public void StringListGettersShouldWork()
{
var a = new A
( p:10
, b: new B
( p: 20
, c : new C(30)));
var a_ = a.Set(p => p.B.C.P, 10);
a_.Get(p=>p.B.C.P).Should().Be(10);
}
}
}
Perhaps reflection based lenses would reduce boiler plate in F#. Maybe
performance could be improved with caching of the accessors or maybe
IL generation.