F# computation expression transparent state passing with Bind - f#

I have the following code that try to read a possibly incomplete data (image data, for example) from a network stream using usual MaybeBuilder:
let image = maybe {
let pos = 2 //Initial position skips 2 bytes of packet ID
let! width, pos = readStreamAsInt 2 pos
let! height, pos = readStreamAsInt 2 pos
let! data, pos = readStream (width*height) pos
advanceInStream pos
return {width = width; height = height; pixels = data}
}
So, readStream[asInt] [numBytes] [offset] function returns Some [data] or None if data has not arrived yet in a NetworkStream. advanceInStream function is executed when whole network packet is read.
I wonder if there is some way to write some custom computation expression builder to hide pos passing from its user, since it's always the same - I read some data and position in stream and pass it to the next read function as a last parameter.
P.S. MaybeBuilder used:
type MaybeBuilder() =
member x.Bind(d,f) = Option.bind f d
member x.Return d = Some d
member x.ReturnFrom d = d
member x.Zero() = None
let maybe = new MaybeBuilder()
P.P.S
On second thought it seems I have to make pos mutable, because of possible "for" or "while" loops in reading. Simple let! works fine with pos Bind shadowing, but you can't hold onto immutability if you add reading in a loop, right? The task becomes trivial then.

#bytebuster is making good points of maintainability about custom computation expressions but I still thought I demonstrate how to combine the State and Maybe monad into one.
In "traditional" languages we have good support for composing values such as integers but we run into problems when developing parsers (Producing values from a binary stream is essentially parsing). For parsers we would like to compose simple parser functions into more complex parser functions but here "traditional" languages often lack good support.
In functional languages functions are as ordinary as values and since values can be composed obviously functions can be as well.
First let's define a StreamReader function. A StreamReader takes a StreamPosition (stream + position) and produces an updated StreamPosition and a StreamReaderResult (the read value or a failure).
type StreamReader<'T> =
StreamReader of (StreamPosition -> StreamPosition*StreamReaderResult<'T>)
(This is the most important step.)
We like to be able to compose simple StreamReader functions into more complex ones. A very important property we want to maintain is that the compose operation is "closed" under StreamReader meaning that result of composition is a new StreamReader which in turn can be composed endlessly.
In order to read an image we need to read the width & height, compute the product and read the bytes. Something like this:
let readImage =
reader {
let! width = readInt32
let! height = readInt32
let! bytes = readBytes (width*height)
return width, height, bytes
}
Because of composition being closed readImage is a StreamReader<int*int*byte[]>.
In order to be able to compose StreamReader like above we need to define a computation expression but before we can do that we need to define the operation Return and Bind for StreamReader. It turns out Yield is good to have as well.
module StreamReader =
let Return v : StreamReader<'T> =
StreamReader <| fun sp ->
sp, (Success v)
let Bind (StreamReader t) (fu : 'T -> StreamReader<'U>) : StreamReader<'U> =
StreamReader <| fun sp ->
let tsp, tr = t sp
match tr with
| Success tv ->
let (StreamReader u) = fu tv
u tsp
| Failure tfs -> tsp, Failure tfs
let Yield (ft : unit -> StreamReader<'T>) : StreamReader<'T> =
StreamReader <| fun sp ->
let (StreamReader t) = ft ()
t sp
Return is trivial as the StreamReader should return the given value and don't update the StreamPosition.
Bind is a bit more challenging but describes how to compose two StreamReader functions into a new one. Bind runs the first StreamReader function and checks the result, if it's a failure it returns a failure otherwise it uses the StreamReader result to compute the second StreamReader and runs that on the update stream position.
Yield just creates the StreamReader function and runs it. Yield is used by F# when building computation expressions.
Finally let's create the computation expression builder
type StreamReaderBuilder() =
member x.Return v = StreamReader.Return v
member x.Bind(t,fu) = StreamReader.Bind t fu
member x.Yield(ft) = StreamReader.Yield ft
let reader = StreamReaderBuilder ()
Now we built the basic framework for combining StreamReader functions. In addition we would we need to define the primitive StreamReader functions.
Full example:
open System
open System.IO
// The result of a stream reader operation is either
// Success of value
// Failure of list of failures
type StreamReaderResult<'T> =
| Success of 'T
| Failure of (string*StreamPosition) list
and StreamPosition =
{
Stream : byte[]
Position : int
}
member x.Remaining = max 0 (x.Stream.Length - x.Position)
member x.ReadBytes (size : int) : StreamPosition*StreamReaderResult<byte[]> =
if x.Remaining < size then
x, Failure ["EOS", x]
else
let nsp = StreamPosition.New x.Stream (x.Position + size)
nsp, Success (x.Stream.[x.Position..(x.Position + size - 1)])
member x.Read (converter : byte[]*int -> 'T) : StreamPosition*StreamReaderResult<'T> =
let size = sizeof<'T>
if x.Remaining < size then
x, Failure ["EOS", x]
else
let nsp = StreamPosition.New x.Stream (x.Position + size)
nsp, Success (converter (x.Stream, x.Position))
static member New s p = {Stream = s; Position = p;}
// Defining the StreamReader<'T> function is the most important decision
// In this case a stream reader is a function that takes a StreamPosition
// and produces a (potentially) new StreamPosition and a StreamReadeResult
type StreamReader<'T> = StreamReader of (StreamPosition -> StreamPosition*StreamReaderResult<'T>)
// Defining the StreamReader CE
module StreamReader =
let Return v : StreamReader<'T> =
StreamReader <| fun sp ->
sp, (Success v)
let Bind (StreamReader t) (fu : 'T -> StreamReader<'U>) : StreamReader<'U> =
StreamReader <| fun sp ->
let tsp, tr = t sp
match tr with
| Success tv ->
let (StreamReader u) = fu tv
u tsp
| Failure tfs -> tsp, Failure tfs
let Yield (ft : unit -> StreamReader<'T>) : StreamReader<'T> =
StreamReader <| fun sp ->
let (StreamReader t) = ft ()
t sp
type StreamReaderBuilder() =
member x.Return v = StreamReader.Return v
member x.Bind(t,fu) = StreamReader.Bind t fu
member x.Yield(ft) = StreamReader.Yield ft
let reader = StreamReaderBuilder ()
let read (StreamReader sr) (bytes : byte[]) (pos : int) : StreamReaderResult<'T> =
let sp = StreamPosition.New bytes pos
let _, sr = sr sp
sr
// Defining various stream reader functions
let readValue (converter : byte[]*int -> 'T) : StreamReader<'T> =
StreamReader <| fun sp -> sp.Read converter
let readInt32 = readValue BitConverter.ToInt32
let readInt16 = readValue BitConverter.ToInt16
let readBytes size : StreamReader<byte[]> =
StreamReader <| fun sp ->
sp.ReadBytes size
let readImage =
reader {
let! width = readInt32
let! height = readInt32
let! bytes = readBytes (width*height)
return width, height, bytes
}
[<EntryPoint>]
let main argv =
// Sample byte stream
let bytes = [|2;0;0;0;3;0;0;0;1;2;3;4;5;6|] |> Array.map byte
let result = read readImage bytes 0
printfn "%A" result
0

Related

Expert f# script compile oddity

On page 209 - 210 there is an extended example (see below) (I'm using F# 4.5).
In summary what I don't understand is: if I type each statement individually, there is a declaration that raises an error. If I submit the whole script at once, with the functions that come after the declaratation that raises the error, everything is OK. So what happens in interactive when I submit all the statements as a batch? Does the function that follows the error get used to create a specific version of the potential generic? The ionide hints do not show a generic for the whole script.
In detail (sorry it's so long)
If you execute each of the statements in order upto and including the declaration of formatP , (or paste all of them upto and including formatP at once - e.g. select and alt-enter with ionide in vs code) in interactive, it produces an error:
binary.fsx(67,5): error FS0030: Value restriction. The value 'formatP' has been inferred to have generic type
val formatP : ((int * bool) list -> '_a -> unit) when '_a :> OutState
Either make the arguments to 'formatP' explicit or, if you do not intend for it to be generic, add a type annotation.
if you paste all of the script including the functions which follow formatP
let writeData file data =
use outStream = BinaryWriter(File.OpenWrite(file))
formatP data outStream
let readData file =
use inStream = BinaryReader(File.OpenRead(file))
formatU inStream
it works without error.
Given that compilation order is important - what is happening here?
i.e. why do the functions that are declared after formatP allow the function to compile.
Whole script - which functions without error (It's a bit long - but because I really don't understand the issue, I'm not sure what I can remove to create an accurate example illustrating what is happening.
I guess I could drop formatU and readData? (which have the same relationship) but they are needed to make the last 2 stamenets work which sahows that the code does complie and execute as expected):
open System.IO
type OutState = BinaryWriter
type InState = BinaryReader
type Pickler<'T> = 'T -> OutState -> unit
type Unpickler<'T> = InState -> 'T
// P is the suffix for pickling and U is the suffix for unpickling
let byteP (b : byte) (st : OutState) = st.Write(b)
let byteU (st : InState) = st.ReadByte()
let boolP b st = byteP (if b then 1uy else 0uy) st
let boolU st = let b = byteU st in (b = 1uy)
let int32P i st =
byteP (byte (i &&& 0xFF)) st
byteP (byte ((i >>> 8) &&& 0xFF)) st
byteP (byte ((i >>> 16) &&& 0xFF)) st
byteP (byte ((i >>> 24) &&& 0xFF)) st
let int32U st =
let b0 = int (byteU st)
let b1 = int (byteU st)
let b2 = int (byteU st)
let b3 = int (byteU st)
b0 ||| (b1 <<< 8) ||| (b2 <<< 16) ||| (b3 <<< 24)
let tup2P p1 p2 (a, b) (st : OutState) =
(p1 a st : unit)
(p2 b st : unit)
let tup3P p1 p2 p3 (a, b, c) (st : OutState) =
(p1 a st : unit)
(p2 b st : unit)
(p3 c st : unit)
let tup2U p1 p2 (st : InState) =
let a = p1 st
let b = p2 st
(a, b)
let tup3U p1 p2 p3 (st : InState) =
let a = p1 st
let b = p2 st
let c = p3 st
(a, b, c)
/// Outputs a list into the given output stream by pickling each element via f.
/// A zero indicates the end of a list, a 1 indicates another element of a list.
let rec listP f lst st =
match lst with
| [] -> byteP 0uy st
| h :: t -> byteP 1uy st; f h st; listP f t st
// Reads a list from a given input stream by unpickling each element via f.
let listU f st =
let rec loop acc =
let tag = byteU st
match tag with
| 0uy -> List.rev acc
| 1uy -> let a = f st in loop (a :: acc)
| n -> failwithf "listU: found number %d" n
loop []
type format = list<int32 * bool>
//the types in these two lines only get fully inferred if the lines after are part of the batch
//eh?
let formatP = listP (tup2P int32P boolP)
let formatU = listU (tup2U int32U boolU)
//IE if you only run to here it is an error
let writeData file data =
use outStream = BinaryWriter(File.OpenWrite(file))
formatP data outStream
let readData file =
use inStream = BinaryReader(File.OpenRead(file))
formatU inStream
//If you run to here it does not error
writeData "out.bin" [(102, true); (108, false)] ;;
readData "out.bin"
There are two things going on here, only one of which I can fully explain.
The first is the F# value restriction. In this case, the compiler infers that listP is a generic function, which also makes the value formatP generic. But F# doesn't allow a generic value in this situation, so a compiler error occurs. However, when writeData is present, formatP is no longer generic, so the compiler error disappears. You can see a very similar situation explained in detail here.
But why does the compiler think listP is generic in the first place? I'm not sure about this. It infers that st must be compatible with OutState, which is correct from an object-oriented point of view. But it expresses this as a generic constraint, using st : #OutState instead of just st : OutState. (F# calls this a "flexible type".) This generic constraint then cascades to formatP, causing the problem you reported. Someone with more knowledge of the F# compiler might be able to explain this.
Here's a very small example that exhibits the same behavior:
type Example() = class end
let alpha (_ : Example) =
()
let beta f x =
alpha (f x)
let gamma = beta id
// let delta = gamma (Example())
The compiler infers a generic type for beta, which makes gamma illegal when delta is commented out.
To make matters stranger, the same problem occurs even if I explicitly annotate beta so it's not generic:
let beta (f : Example -> Example) (x : Example) =
alpha (f x)
So the compiler thinks gamma is generic even when beta definitely isn't generic. I don't know why that is.

How do I write a computation expression builder that accumulates a value and also allows standard language constructs?

I have a computation expression builder that builds up a value as you go, and has many custom operations. However, it does not allow for standard F# language constructs, and I'm having a lot of trouble figuring out how to add this support.
To give a stand-alone example, here's a dead-simple and fairly pointless computation expression that builds F# lists:
type Items<'a> = Items of 'a list
type ListBuilder() =
member x.Yield(()) = Items []
[<CustomOperation("add")>]
member x.Add(Items current, item:'a) =
Items [ yield! current; yield item ]
[<CustomOperation("addMany")>]
member x.AddMany(Items current, items: seq<'a>) =
Items [ yield! current; yield! items ]
let listBuilder = ListBuilder()
let build (Items items) = items
I can use this to build lists just fine:
let stuff =
listBuilder {
add 1
add 5
add 7
addMany [ 1..10 ]
add 42
}
|> build
However, this is a compiler error:
listBuilder {
let x = 5 * 39
add x
}
// This expression was expected to have type unit, but
// here has type int.
And so is this:
listBuilder {
for x = 1 to 50 do
add x
}
// This control construct may only be used if the computation expression builder
// defines a For method.
I've read all the documentation and examples I can find, but there's something I'm just not getting. Every .Bind() or .For() method signature I try just leads to more and more confusing compiler errors. Most of the examples I can find either build up a value as you go along, or allow for regular F# language constructs, but I haven't been able to find one that does both.
If someone could point me in the right direction by showing me how to take this example and add support in the builder for let bindings and for loops (at minimum - using, while and try/catch would be great, but I can probably figure those out if someone gets me started) then I'll be able to gratefully apply the lesson to my actual problem.
The best place to look is the spec. For example,
b {
let x = e
op x
}
gets translated to
T(let x = e in op x, [], fun v -> v, true)
=> T(op x, {x}, fun v -> let x = e in v, true)
=> [| op x, let x = e in b.Yield(x) |]{x}
=> b.Op(let x = e in in b.Yield(x), x)
So this shows where things have gone wrong, though it doesn't present an obvious solution. Clearly, Yield needs to be generalized since it needs to take arbitrary tuples (based on how many variables are in scope). Perhaps more subtly, it also shows that x is not in scope in the call to add (see that unbound x as the second argument to b.Op?). To allow your custom operators to use bound variables, their arguments need to have the [<ProjectionParameter>] attribute (and take functions from arbitrary variables as arguments), and you'll also need to set MaintainsVariableSpace to true if you want bound variables to be available to later operators. This will change the final translation to:
b.Op(let x = e in b.Yield(x), fun x -> x)
Building up from this, it seems that there's no way to avoid passing the set of bound values along to and from each operation (though I'd love to be proven wrong) - this will require you to add a Run method to strip those values back off at the end. Putting it all together, you'll get a builder which looks like this:
type ListBuilder() =
member x.Yield(vars) = Items [],vars
[<CustomOperation("add",MaintainsVariableSpace=true)>]
member x.Add((Items current,vars), [<ProjectionParameter>]f) =
Items (current # [f vars]),vars
[<CustomOperation("addMany",MaintainsVariableSpace=true)>]
member x.AddMany((Items current, vars), [<ProjectionParameter>]f) =
Items (current # f vars),vars
member x.Run(l,_) = l
The most complete examples I've seen are in §6.3.10 of the spec, especially this one:
/// Computations that can cooperatively yield by returning a continuation
type Eventually<'T> =
| Done of 'T
| NotYetDone of (unit -> Eventually<'T>)
[<CompilationRepresentation(CompilationRepresentationFlags.ModuleSuffix)>]
module Eventually =
/// The bind for the computations. Stitch 'k' on to the end of the computation.
/// Note combinators like this are usually written in the reverse way,
/// for example,
/// e |> bind k
let rec bind k e =
match e with
| Done x -> NotYetDone (fun () -> k x)
| NotYetDone work -> NotYetDone (fun () -> bind k (work()))
/// The return for the computations.
let result x = Done x
type OkOrException<'T> =
| Ok of 'T
| Exception of System.Exception
/// The catch for the computations. Stitch try/with throughout
/// the computation and return the overall result as an OkOrException.
let rec catch e =
match e with
| Done x -> result (Ok x)
| NotYetDone work ->
NotYetDone (fun () ->
let res = try Ok(work()) with | e -> Exception e
match res with
| Ok cont -> catch cont // note, a tailcall
| Exception e -> result (Exception e))
/// The delay operator.
let delay f = NotYetDone (fun () -> f())
/// The stepping action for the computations.
let step c =
match c with
| Done _ -> c
| NotYetDone f -> f ()
// The rest of the operations are boilerplate.
/// The tryFinally operator.
/// This is boilerplate in terms of "result", "catch" and "bind".
let tryFinally e compensation =
catch (e)
|> bind (fun res -> compensation();
match res with
| Ok v -> result v
| Exception e -> raise e)
/// The tryWith operator.
/// This is boilerplate in terms of "result", "catch" and "bind".
let tryWith e handler =
catch e
|> bind (function Ok v -> result v | Exception e -> handler e)
/// The whileLoop operator.
/// This is boilerplate in terms of "result" and "bind".
let rec whileLoop gd body =
if gd() then body |> bind (fun v -> whileLoop gd body)
else result ()
/// The sequential composition operator
/// This is boilerplate in terms of "result" and "bind".
let combine e1 e2 =
e1 |> bind (fun () -> e2)
/// The using operator.
let using (resource: #System.IDisposable) f =
tryFinally (f resource) (fun () -> resource.Dispose())
/// The forLoop operator.
/// This is boilerplate in terms of "catch", "result" and "bind".
let forLoop (e:seq<_>) f =
let ie = e.GetEnumerator()
tryFinally (whileLoop (fun () -> ie.MoveNext())
(delay (fun () -> let v = ie.Current in f v)))
(fun () -> ie.Dispose())
// Give the mapping for F# computation expressions.
type EventuallyBuilder() =
member x.Bind(e,k) = Eventually.bind k e
member x.Return(v) = Eventually.result v
member x.ReturnFrom(v) = v
member x.Combine(e1,e2) = Eventually.combine e1 e2
member x.Delay(f) = Eventually.delay f
member x.Zero() = Eventually.result ()
member x.TryWith(e,handler) = Eventually.tryWith e handler
member x.TryFinally(e,compensation) = Eventually.tryFinally e compensation
member x.For(e:seq<_>,f) = Eventually.forLoop e f
member x.Using(resource,e) = Eventually.using resource e
The tutorial at "F# for fun and profit" is first class in this regard.
http://fsharpforfunandprofit.com/posts/computation-expressions-intro/
Following a similar struggle to Joel's (and not finding §6.3.10 of the spec that helpful) my issue with getting the For construct to generate a list came down to getting types to line up properly (no special attributes required). In particular I was slow to realise that For would build a list of lists, and therefore need flattening, despite the best efforts of the compiler to put me right. Examples that I found on the web were always wrappers around seq{}, using the yield keyword, repeated use of which invokes a call to Combine, which does the flattening. In case a concrete example helps, the following excerpt uses for to build a list of integers - my ultimate aim being to create lists of components for rendering in a GUI (with some additional laziness thrown in). Also In depth talk on CE here which elaborates on kvb's points above.
module scratch
type Dispatcher = unit -> unit
type viewElement = int
type lazyViews = Lazy<list<viewElement>>
type ViewElementsBuilder() =
member x.Return(views: lazyViews) : list<viewElement> = views.Value
member x.Yield(v: viewElement) : list<viewElement> = [v]
member x.ReturnFrom(viewElements: list<viewElement>) = viewElements
member x.Zero() = list<viewElement>.Empty
member x.Combine(listA:list<viewElement>, listB: list<viewElement>) = List.concat [listA; listB]
member x.Delay(f) = f()
member x.For(coll:seq<'a>, forBody: 'a -> list<viewElement>) : list<viewElement> =
// seq {for v in coll do yield! f v} |> List.ofSeq
Seq.map forBody coll |> Seq.collect id |> List.ofSeq
let ve = new ViewElementsBuilder()
let makeComponent(m: int, dispatch: Dispatcher) : viewElement = m
let makeComponents() : list<viewElement> = [77; 33]
let makeViewElements() : list<viewElement> =
let model = {| Scores = [33;23;22;43;] |> Seq.ofList; Trainer = "John" |}
let d:Dispatcher = fun() -> () // Does nothing here, but will be used to raise messages from UI
ve {
for score in model.Scores do
yield makeComponent (score, d)
yield makeComponent (score * 100 / 50 , d)
if model.Trainer = "John" then
return lazy
[ makeComponent (12, d)
makeComponent (13, d)
]
else
return lazy
[ makeComponent (14, d)
makeComponent (15, d)
]
yield makeComponent (33, d)
return! makeComponents()
}

Wrangling TryWith in Computation expressions

(Having failed to 'grok' FParsec, I followed the advice I read somewhere and started trying to write a little parser myself. Somehow I spotted what looked like a chance to try and monadify it, and now I have N problems...)
This is my 'Result' type (simplified)
type Result<'a> =
| Success of 'a
| Failure of string
Here's the computation expression builder
type ResultBuilder() =
member m.Return a = Success(a)
member m.Bind(r,fn) =
match r with
| Success(a) -> fn a
| Failure(m) -> Failure(m)
In this first example, everything works (compiles) as expected:
module Parser =
let res = ResultBuilder()
let Combine p1 p2 fn =
fun a -> res { let! x = p1 a
let! y = p2 a
return fn(x,y) }
My problem is here: I'd like to be able to catch any failure in the 'combining' function and return a failure, but it says that I should define a 'Zero'.
let Combine2 p1 p2 fn =
fun a -> res { let! x = p1 a
let! y = p2 a
try
return fn(x,y)
with
| ex -> Failure(ex.Message) }
Having no idea what I should return in a Zero, I just threw in member m.Zero() = Failure("hello world"), and it now says I need TryWith.
So:
member m.TryWith(r,fn) =
try
r()
with
| ex -> fn ex
And now it wants Delay, so member m.Delay f = (fun () -> f()).
At which point it says (on the ex -> Failure), This expression should have type 'unit', but has type 'Result<'a>', and I throw up my arms and turn to you guys...
Link for playing: http://dotnetfiddle.net/Ho1sGS
The with block should also return a result from the computation expression. Since you want to return Result.Failure you need to define the member m.ReturnFrom a = a and use it to return the Failure from the with block. In the try block you should also specify that fn returns Success if it doesn't throw.
let Combine2 p1 p2 fn =
fun a -> res { let! x = p1 a
let! y = p2 a
return!
try
Success(fn(x,y))
with
| ex -> Failure(ex.Message)
}
Update:
The original implementation was showing a warning, not an error. The expression in the with block was not used since you returned from the try block, so you could simply add |> ignore. In that case if fn throws then the return value is m.Zero() and the only difference is that you would get "hello world" instead of ex.Message. Illustrated with an example below. Full script here: http://dotnetfiddle.net/mFbeZg
Original implementation with |> ignore to mute the warning:
let Combine3 p1 p2 fn =
fun a -> res { let! x = p1 a
let! y = p2 a
try
return fn(x,y)
with
| ex -> Failure(ex.Message) |> ignore // no warning
}
Run it:
let comb2 a =
let p1' x = Success(x)
let p2' y = Success(y)
let fn' (x,y) = 1/0 // div by zero
let func = Parser.Combine2 p1' p2' fn' a
func()
let comb3 a =
let p1' x = Success(x)
let p2' y = Success(y)
let fn' (x,y) = 1/0 // div by zero
let func = Parser.Combine3 p1' p2' fn' a
func()
let test2 = comb2 1
let test3 = comb3 1
Result:
val test2 : Result<int> = Failure "Attempted to divide by zero."
val test3 : Result<int> = Failure "hello world"
If you want to support try ... with inside a computation builder, you need to add TryWith (as you tried) as well as a few other members including Delay and Run (depending on how you want to implement Delay). In order to be able to return failure, you also need to support return! by adding ReturnFrom:
type ResultBuilder() =
member m.Return a = Success(a)
member m.Bind(r,fn) =
match r with
| Success(a) -> fn a
| Failure(m) -> Failure(m)
member m.TryWith(r,fn) =
try r() with ex -> fn ex
member m.Delay(f) = f
member m.Run(f) = f()
member m.ReturnFrom(r) = r
Now you can do the following:
let Combine2 p1 p2 fn = fun a -> res {
let! x = p1 a
let! y = p2 a
try
return fn(x,y)
with ex ->
return! Failure(ex.Message) }
The trick is that the normal branch uses just return (representing success), but the exception handler uses return! to return an explicitly created result using Failure.
That said, if you are interested in parsers, then you need to use a different type - what you are describing here is more like the option (or Maybe) monad. To implement parser combinators you need a type that represents a parser rather than result of a parser. See for example this article.

F# compose pattern matched function

I have these types:
type ShouldRetry = ShouldRetry of (RetryCount * LastException -> bool * RetryDelay)
and RetryCount = int
and LastException = exn
and RetryDelay = TimeSpan
type RetryPolicy = RetryPolicy of ShouldRetry
Now I want composability of the retries; something like this:
let serverOverloaded = [| exnRetry<TimeoutException>;
exnRetry<ServerBusyException> |]
|> Array.map (fun fn -> fn (TimeSpan.FromSeconds(4.0)))
let badNetwork = [||] // etc
let compose p1 p2 =
// http://fssnip.net/7h
RetryPolicy(ShouldRetry( (fun (c,e) ->
let RetryPolicy(ShouldRetry(fn)) = p1
let RetryPolicy(ShouldRetry(fn')) = p2
let (cont, delay) = fn c,e
if cont then cont, delay
else
let (cont', delay') = fn' c,e
cont', delay') ))
let finalPolicy = serverOverloaded |> Array.scan compose (RetryPolicies.NoRetry())
But I'm getting compiler errors on fn, delay and fn', saying "The value or constructor 'fn' is not defined".
I can see two problems in your compose function.
When decomposing p1 and p2, the pattern needs to be wrapped in parentheses (otherwise, the compiler interprets the code as a definition of RetryPolicy function, instead of pattern matching):
let (RetryPolicy(ShouldRetry(fn))) = p1
let (RetryPolicy(ShouldRetry(fn'))) = p2
When calling fn' a bit later, you need to pass it the arguments in a tuple (otherwise, the compiler thinks that you're calling fn' with just a single argument c and then building a tuple):
let (cont', delay') = fn' (c,e)
I didn't check (or tried to run) the whole example, so I don't know if the rest of the code does what you want.

Handy F# snippets [closed]

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Closed 10 years ago.
There are already two questions about F#/functional snippets.
However what I'm looking for here are useful snippets, little 'helper' functions that are reusable. Or obscure but nifty patterns that you can never quite remember.
Something like:
open System.IO
let rec visitor dir filter=
seq { yield! Directory.GetFiles(dir, filter)
for subdir in Directory.GetDirectories(dir) do
yield! visitor subdir filter}
I'd like to make this a kind of handy reference page. As such there will be no right answer, but hopefully lots of good ones.
EDIT Tomas Petricek has created a site specifically for F# snippets http://fssnip.net/.
Perl style regex matching
let (=~) input pattern =
System.Text.RegularExpressions.Regex.IsMatch(input, pattern)
It lets you match text using let test = "monkey" =~ "monk.+" notation.
Infix Operator
I got this from http://sandersn.com/blog//index.php/2009/10/22/infix-function-trick-for-f go to that page for more details.
If you know Haskell, you might find yourself missing infix sugar in F#:
// standard Haskell call has function first, then args just like F#. So obviously
// here there is a function that takes two strings: string -> string -> string
startsWith "kevin" "k"
//Haskell infix operator via backQuotes. Sometimes makes a function read better.
"kevin" `startsWith` "K"
While F# doesn't have a true 'infix' operator, the same thing can be accomplished almost as elegantly via a pipeline and a 'backpipeline' (who knew of such a thing??)
// F# 'infix' trick via pipelines
"kevin" |> startsWith <| "K"
Multi-Line Strings
This is pretty trivial, but it seems to be a feature of F# strings that is not widely known.
let sql = "select a,b,c \
from table \
where a = 1"
This produces:
val sql : string = "select a,b,c from table where a = 1"
When the F# compiler sees a back-slash followed by a carriage return inside a string literal, it will remove everything from the back-slash to the first non-space character on the next line. This allows you to have multi-line string literals that line up, without using a bunch of string concatenation.
Generic memoization, courtesy of the man himself
let memoize f =
let cache = System.Collections.Generic.Dictionary<_,_>(HashIdentity.Structural)
fun x ->
let ok, res = cache.TryGetValue(x)
if ok then res
else let res = f x
cache.[x] <- res
res
Using this, you could do a cached reader like so:
let cachedReader = memoize reader
Simple read-write to text files
These are trivial, but make file access pipeable:
open System.IO
let fileread f = File.ReadAllText(f)
let filewrite f s = File.WriteAllText(f, s)
let filereadlines f = File.ReadAllLines(f)
let filewritelines f ar = File.WriteAllLines(f, ar)
So
let replace f (r:string) (s:string) = s.Replace(f, r)
"C:\\Test.txt" |>
fileread |>
replace "teh" "the" |>
filewrite "C:\\Test.txt"
And combining that with the visitor quoted in the question:
let filereplace find repl path =
path |> fileread |> replace find repl |> filewrite path
let recurseReplace root filter find repl =
visitor root filter |> Seq.iter (filereplace find repl)
Update Slight improvement if you want to be able to read 'locked' files (e.g. csv files which are already open in Excel...):
let safereadall f =
use fs = new FileStream(f, FileMode.Open, FileAccess.Read, FileShare.ReadWrite)
use sr = new StreamReader(fs, System.Text.Encoding.Default)
sr.ReadToEnd()
let split sep (s:string) = System.Text.RegularExpressions.Regex.Split(s, sep)
let fileread f = safereadall f
let filereadlines f = f |> safereadall |> split System.Environment.NewLine
For performance intensive stuff where you need to check for null
let inline isNull o = System.Object.ReferenceEquals(o, null)
if isNull o then ... else ...
Is about 20x faster then
if o = null then ... else ...
Active Patterns, aka "Banana Splits", are a very handy construct that let one match against multiple regular expression patterns. This is much like AWK, but without the high performance of DFA's because the patterns are matched in sequence until one succeeds.
#light
open System
open System.Text.RegularExpressions
let (|Test|_|) pat s =
if (new Regex(pat)).IsMatch(s)
then Some()
else None
let (|Match|_|) pat s =
let opt = RegexOptions.None
let re = new Regex(pat,opt)
let m = re.Match(s)
if m.Success
then Some(m.Groups)
else None
Some examples of use:
let HasIndefiniteArticle = function
| Test "(?: |^)(a|an)(?: |$)" _ -> true
| _ -> false
type Ast =
| IntVal of string * int
| StringVal of string * string
| LineNo of int
| Goto of int
let Parse = function
| Match "^LET\s+([A-Z])\s*=\s*(\d+)$" g ->
IntVal( g.[1].Value, Int32.Parse(g.[2].Value) )
| Match "^LET\s+([A-Z]\$)\s*=\s*(.*)$" g ->
StringVal( g.[1].Value, g.[2].Value )
| Match "^(\d+)\s*:$" g ->
LineNo( Int32.Parse(g.[1].Value) )
| Match "^GOTO \s*(\d+)$" g ->
Goto( Int32.Parse(g.[1].Value) )
| s -> failwithf "Unexpected statement: %s" s
Maybe monad
type maybeBuilder() =
member this.Bind(v, f) =
match v with
| None -> None
| Some(x) -> f x
member this.Delay(f) = f()
member this.Return(v) = Some v
let maybe = maybeBuilder()
Here's a brief intro to monads for the uninitiated.
Option-coalescing operators
I wanted a version of the defaultArg function that had a syntax closer to the C# null-coalescing operator, ??. This lets me get the value from an Option while providing a default value, using a very concise syntax.
/// Option-coalescing operator - this is like the C# ?? operator, but works with
/// the Option type.
/// Warning: Unlike the C# ?? operator, the second parameter will always be
/// evaluated.
/// Example: let foo = someOption |? default
let inline (|?) value defaultValue =
defaultArg value defaultValue
/// Option-coalescing operator with delayed evaluation. The other version of
/// this operator always evaluates the default value expression. If you only
/// want to create the default value when needed, use this operator and pass
/// in a function that creates the default.
/// Example: let foo = someOption |?! (fun () -> new Default())
let inline (|?!) value f =
match value with Some x -> x | None -> f()
'Unitize' a function which doesn't handle units
Using the FloatWithMeasure function http://msdn.microsoft.com/en-us/library/ee806527(VS.100).aspx.
let unitize (f:float -> float) (v:float<'u>) =
LanguagePrimitives.FloatWithMeasure<'u> (f (float v))
Example:
[<Measure>] type m
[<Measure>] type kg
let unitize (f:float -> float) (v:float<'u>) =
LanguagePrimitives.FloatWithMeasure<'u> (f (float v))
//this function doesn't take units
let badinc a = a + 1.
//this one does!
let goodinc v = unitize badinc v
goodinc 3.<m>
goodinc 3.<kg>
OLD version:
let unitize (f:float -> float) (v:float<'u>) =
let unit = box 1. :?> float<'u>
unit * (f (v/unit))
Kudos to kvb
Scale/Ratio function builder
Again, trivial, but handy.
//returns a function which will convert from a1-a2 range to b1-b2 range
let scale (a1:float<'u>, a2:float<'u>) (b1:float<'v>,b2:float<'v>) =
let m = (b2 - b1)/(a2 - a1) //gradient of line (evaluated once only..)
(fun a -> b1 + m * (a - a1))
Example:
[<Measure>] type m
[<Measure>] type px
let screenSize = (0.<px>, 300.<px>)
let displayRange = (100.<m>, 200.<m>)
let scaleToScreen = scale displayRange screenSize
scaleToScreen 120.<m> //-> 60.<px>
Transposing a list (seen on Jomo Fisher's blog)
///Given list of 'rows', returns list of 'columns'
let rec transpose lst =
match lst with
| (_::_)::_ -> List.map List.head lst :: transpose (List.map List.tail lst)
| _ -> []
transpose [[1;2;3];[4;5;6];[7;8;9]] // returns [[1;4;7];[2;5;8];[3;6;9]]
And here is a tail-recursive version which (from my sketchy profiling) is mildly slower, but has the advantage of not throwing a stack overflow when the inner lists are longer than 10000 elements (on my machine):
let transposeTR lst =
let rec inner acc lst =
match lst with
| (_::_)::_ -> inner (List.map List.head lst :: acc) (List.map List.tail lst)
| _ -> List.rev acc
inner [] lst
If I was clever, I'd try and parallelise it with async...
F# Map <-> C# Dictionary
(I know, I know, System.Collections.Generic.Dictionary isn't really a 'C#' dictionary)
C# to F#
(dic :> seq<_>) //cast to seq of KeyValuePair
|> Seq.map (|KeyValue|) //convert KeyValuePairs to tuples
|> Map.ofSeq //convert to Map
(From Brian, here, with improvement proposed by Mauricio in comment below. (|KeyValue|) is an active pattern for matching KeyValuePair - from FSharp.Core - equivalent to (fun kvp -> kvp.Key, kvp.Value))
Interesting alternative
To get all of the immutable goodness, but with the O(1) lookup speed of Dictionary, you can use the dict operator, which returns an immutable IDictionary (see this question).
I currently can't see a way to directly convert a Dictionary using this method, other than
(dic :> seq<_>) //cast to seq of KeyValuePair
|> (fun kvp -> kvp.Key, kvp.Value) //convert KeyValuePairs to tuples
|> dict //convert to immutable IDictionary
F# to C#
let dic = Dictionary()
map |> Map.iter (fun k t -> dic.Add(k, t))
dic
What is weird here is that FSI will report the type as (for example):
val it : Dictionary<string,int> = dict [("a",1);("b",2)]
but if you feed dict [("a",1);("b",2)] back in, FSI reports
IDictionary<string,int> = seq[[a,1] {Key = "a"; Value = 1; } ...
Tree-sort / Flatten a tree into a list
I have the following binary tree:
___ 77 _
/ \
______ 47 __ 99
/ \
21 _ 54
\ / \
43 53 74
/
39
/
32
Which is represented as follows:
type 'a tree =
| Node of 'a tree * 'a * 'a tree
| Nil
let myTree =
Node
(Node
(Node (Nil,21,Node (Node (Node (Nil,32,Nil),39,Nil),43,Nil)),47,
Node (Node (Nil,53,Nil),54,Node (Nil,74,Nil))),77,Node (Nil,99,Nil))
A straightforward method to flatten the tree is:
let rec flatten = function
| Nil -> []
| Node(l, a, r) -> flatten l # a::flatten r
This isn't tail-recursive, and I believe the # operator causes it to be O(n log n) or O(n^2) with unbalanced binary trees. With a little tweaking, I came up with this tail-recursive O(n) version:
let flatten2 t =
let rec loop acc c = function
| Nil -> c acc
| Node(l, a, r) ->
loop acc (fun acc' -> loop (a::acc') c l) r
loop [] (fun x -> x) t
Here's the output in fsi:
> flatten2 myTree;;
val it : int list = [21; 32; 39; 43; 47; 53; 54; 74; 77; 99]
LINQ-to-XML helpers
namespace System.Xml.Linq
// hide warning about op_Explicit
#nowarn "77"
[<AutoOpen>]
module XmlUtils =
/// Converts a string to an XName.
let xn = XName.op_Implicit
/// Converts a string to an XNamespace.
let xmlns = XNamespace.op_Implicit
/// Gets the string value of any XObject subclass that has a Value property.
let inline xstr (x : ^a when ^a :> XObject) =
(^a : (member get_Value : unit -> string) x)
/// Gets a strongly-typed value from any XObject subclass, provided that
/// an explicit conversion to the output type has been defined.
/// (Many explicit conversions are defined on XElement and XAttribute)
/// Example: let value:int = xval foo
let inline xval (x : ^a when ^a :> XObject) : ^b =
((^a or ^b) : (static member op_Explicit : ^a -> ^b) x)
/// Dynamic lookup operator for getting an attribute value from an XElement.
/// Returns a string option, set to None if the attribute was not present.
/// Example: let value = foo?href
/// Example with default: let value = defaultArg foo?Name "<Unknown>"
let (?) (el:XElement) (name:string) =
match el.Attribute(xn name) with
| null -> None
| att -> Some(att.Value)
/// Dynamic operator for setting an attribute on an XElement.
/// Example: foo?href <- "http://www.foo.com/"
let (?<-) (el:XElement) (name:string) (value:obj) =
el.SetAttributeValue(xn name, value)
OK, this has nothing to do with snippets, but I keep forgetting this:
If you are in the interactive window, you hit F7 to jump back to the code window (without deselecting the code which you just ran...)
Going from code window to F# window (and also to open the F# window) is Ctrl Alt F
(unless CodeRush has stolen your bindings...)
Weighted sum of arrays
Calculating a weighted [n-array] sum of a [k-array of n-arrays] of numbers, based on a [k-array] of weights
(Copied from this question, and kvb's answer)
Given these arrays
let weights = [|0.6;0.3;0.1|]
let arrs = [| [|0.0453;0.065345;0.07566;1.562;356.6|] ;
[|0.0873;0.075565;0.07666;1.562222;3.66|] ;
[|0.06753;0.075675;0.04566;1.452;3.4556|] |]
We want a weighted sum (by column), given that both dimensions of the arrays can be variable.
Array.map2 (fun w -> Array.map ((*) w)) weights arrs
|> Array.reduce (Array.map2 (+))
First line: Partial application of the first Array.map2 function to weights yields a new function (Array.map ((*) weight) which is applied (for each weight) to each array in arr.
Second line: Array.reduce is like fold, except it starts on the second value and uses the first as the initial 'state'. In this case each value is a 'line' of our array of arrays. So applying an Array.map2 (+) on the first two lines means that we sum the first two arrays, which leaves us with a new array, which we then (Array.reduce) sum again onto the next (in this case last) array.
Result:
[|0.060123; 0.069444; 0.07296; 1.5510666; 215.40356|]
Performance testing
(Found here and updated for latest release of F#)
open System
open System.Diagnostics
module PerformanceTesting =
let Time func =
let stopwatch = new Stopwatch()
stopwatch.Start()
func()
stopwatch.Stop()
stopwatch.Elapsed.TotalMilliseconds
let GetAverageTime timesToRun func =
Seq.initInfinite (fun _ -> (Time func))
|> Seq.take timesToRun
|> Seq.average
let TimeOperation timesToRun =
GC.Collect()
GetAverageTime timesToRun
let TimeOperations funcsWithName =
let randomizer = new Random(int DateTime.Now.Ticks)
funcsWithName
|> Seq.sortBy (fun _ -> randomizer.Next())
|> Seq.map (fun (name, func) -> name, (TimeOperation 100000 func))
let TimeOperationsAFewTimes funcsWithName =
Seq.initInfinite (fun _ -> (TimeOperations funcsWithName))
|> Seq.take 50
|> Seq.concat
|> Seq.groupBy fst
|> Seq.map (fun (name, individualResults) -> name, (individualResults |> Seq.map snd |> Seq.average))
DataSetExtensions for F#, DataReaders
System.Data.DataSetExtensions.dll adds the ability to treat a DataTable as an IEnumerable<DataRow> as well as unboxing the values of individual cells in a way that gracefully handles DBNull by supporting System.Nullable. For example, in C# we can get the value of an integer column that contains nulls, and specify that DBNull should default to zero with a very concise syntax:
var total = myDataTable.AsEnumerable()
.Select(row => row.Field<int?>("MyColumn") ?? 0)
.Sum();
There are two areas where DataSetExtensions are lacking, however. First, it doesn't support IDataReader and second, it doesn't support the F# option type. The following code does both - it allows an IDataReader to be treated as a seq<IDataRecord>, and it can unbox values from either a reader or a dataset, with support for F# options or System.Nullable. Combined with the option-coalescing operator in another answer, this allows for code such as the following when working with a DataReader:
let total =
myReader.AsSeq
|> Seq.map (fun row -> row.Field<int option>("MyColumn") |? 0)
|> Seq.sum
Perhaps a more idiomatic F# way of ignoring database nulls would be...
let total =
myReader.AsSeq
|> Seq.choose (fun row -> row.Field<int option>("MyColumn"))
|> Seq.sum
Further, the extension methods defined below are usable from both F# and from C#/VB.
open System
open System.Data
open System.Reflection
open System.Runtime.CompilerServices
open Microsoft.FSharp.Collections
/// Ported from System.Data.DatasetExtensions.dll to add support for the Option type.
[<AbstractClass; Sealed>]
type private UnboxT<'a> private () =
// This class generates a converter function based on the desired output type,
// and then re-uses the converter function forever. Because the class itself is generic,
// different output types get different cached converter functions.
static let referenceField (value:obj) =
if value = null || DBNull.Value.Equals(value) then
Unchecked.defaultof<'a>
else
unbox value
static let valueField (value:obj) =
if value = null || DBNull.Value.Equals(value) then
raise <| InvalidCastException("Null cannot be converted to " + typeof<'a>.Name)
else
unbox value
static let makeConverter (target:Type) methodName =
Delegate.CreateDelegate(typeof<Converter<obj,'a>>,
typeof<UnboxT<'a>>
.GetMethod(methodName, BindingFlags.NonPublic ||| BindingFlags.Static)
.MakeGenericMethod([| target.GetGenericArguments().[0] |]))
|> unbox<Converter<obj,'a>>
|> FSharpFunc.FromConverter
static let unboxFn =
let theType = typeof<'a>
if theType.IsGenericType && not theType.IsGenericTypeDefinition then
let genericType = theType.GetGenericTypeDefinition()
if typedefof<Nullable<_>> = genericType then
makeConverter theType "NullableField"
elif typedefof<option<_>> = genericType then
makeConverter theType "OptionField"
else
invalidOp "The only generic types supported are Option<T> and Nullable<T>."
elif theType.IsValueType then
valueField
else
referenceField
static member private NullableField<'b when 'b : struct and 'b :> ValueType and 'b:(new:unit -> 'b)> (value:obj) =
if value = null || DBNull.Value.Equals(value) then
Nullable<_>()
else
Nullable<_>(unbox<'b> value)
static member private OptionField<'b> (value:obj) =
if value = null || DBNull.Value.Equals(value) then
None
else
Some(unbox<'b> value)
static member inline Unbox =
unboxFn
/// F# data-related extension methods.
[<AutoOpen>]
module FsDataEx =
type System.Data.IDataReader with
/// Exposes a reader's current result set as seq<IDataRecord>.
/// Reader is closed when sequence is fully enumerated.
member this.AsSeq =
seq { use reader = this
while reader.Read() do yield reader :> IDataRecord }
/// Exposes all result sets in a reader as seq<seq<IDataRecord>>.
/// Reader is closed when sequence is fully enumerated.
member this.AsMultiSeq =
let rowSeq (reader:IDataReader) =
seq { while reader.Read() do yield reader :> IDataRecord }
seq {
use reader = this
yield rowSeq reader
while reader.NextResult() do
yield rowSeq reader
}
/// Populates a new DataSet with the contents of the reader. Closes the reader after completion.
member this.ToDataSet () =
use reader = this
let dataSet = new DataSet(RemotingFormat=SerializationFormat.Binary, EnforceConstraints=false)
dataSet.Load(reader, LoadOption.OverwriteChanges, [| "" |])
dataSet
type System.Data.IDataRecord with
/// Gets a value from the record by name.
/// DBNull and null are returned as the default value for the type.
/// Supports both nullable and option types.
member this.Field<'a> (fieldName:string) =
this.[fieldName] |> UnboxT<'a>.Unbox
/// Gets a value from the record by column index.
/// DBNull and null are returned as the default value for the type.
/// Supports both nullable and option types.
member this.Field<'a> (ordinal:int) =
this.GetValue(ordinal) |> UnboxT<'a>.Unbox
type System.Data.DataRow with
/// Identical to the Field method from DatasetExtensions, but supports the F# Option type.
member this.Field2<'a> (columnName:string) =
this.[columnName] |> UnboxT<'a>.Unbox
/// Identical to the Field method from DatasetExtensions, but supports the F# Option type.
member this.Field2<'a> (columnIndex:int) =
this.[columnIndex] |> UnboxT<'a>.Unbox
/// Identical to the Field method from DatasetExtensions, but supports the F# Option type.
member this.Field2<'a> (column:DataColumn) =
this.[column] |> UnboxT<'a>.Unbox
/// Identical to the Field method from DatasetExtensions, but supports the F# Option type.
member this.Field2<'a> (columnName:string, version:DataRowVersion) =
this.[columnName, version] |> UnboxT<'a>.Unbox
/// Identical to the Field method from DatasetExtensions, but supports the F# Option type.
member this.Field2<'a> (columnIndex:int, version:DataRowVersion) =
this.[columnIndex, version] |> UnboxT<'a>.Unbox
/// Identical to the Field method from DatasetExtensions, but supports the F# Option type.
member this.Field2<'a> (column:DataColumn, version:DataRowVersion) =
this.[column, version] |> UnboxT<'a>.Unbox
/// C# data-related extension methods.
[<Extension; AbstractClass; Sealed>]
type CsDataEx private () =
/// Populates a new DataSet with the contents of the reader. Closes the reader after completion.
[<Extension>]
static member ToDataSet(this:IDataReader) =
this.ToDataSet()
/// Exposes a reader's current result set as IEnumerable{IDataRecord}.
/// Reader is closed when sequence is fully enumerated.
[<Extension>]
static member AsEnumerable(this:IDataReader) =
this.AsSeq
/// Exposes all result sets in a reader as IEnumerable{IEnumerable{IDataRecord}}.
/// Reader is closed when sequence is fully enumerated.
[<Extension>]
static member AsMultipleEnumerable(this:IDataReader) =
this.AsMultiSeq
/// Gets a value from the record by name.
/// DBNull and null are returned as the default value for the type.
/// Supports both nullable and option types.
[<Extension>]
static member Field<'T> (this:IDataRecord, fieldName:string) =
this.Field<'T>(fieldName)
/// Gets a value from the record by column index.
/// DBNull and null are returned as the default value for the type.
/// Supports both nullable and option types.
[<Extension>]
static member Field<'T> (this:IDataRecord, ordinal:int) =
this.Field<'T>(ordinal)
Handling arguments in a command line application:
//We assume that the actual meat is already defined in function
// DoStuff (string -> string -> string -> unit)
let defaultOutOption = "N"
let defaultUsageOption = "Y"
let usage =
"Scans a folder for and outputs results.\n" +
"Usage:\n\t MyApplication.exe FolderPath [IncludeSubfolders (Y/N) : default=" +
defaultUsageOption + "] [OutputToFile (Y/N): default=" + defaultOutOption + "]"
let HandlArgs arr =
match arr with
| [|d;u;o|] -> DoStuff d u o
| [|d;u|] -> DoStuff d u defaultOutOption
| [|d|] -> DoStuff d defaultUsageOption defaultOutOption
| _ ->
printf "%s" usage
Console.ReadLine() |> ignore
[<EntryPoint>]
let main (args : string array) =
args |> HandlArgs
0
(I had a vague memory of this technique being inspired by Robert Pickering, but can't find a reference now)
A handy cache function that keeps up to max (key,reader(key)) in a dictionary and use a SortedList to track the MRU keys
let Cache (reader: 'key -> 'value) max =
let cache = new Dictionary<'key,LinkedListNode<'key * 'value>>()
let keys = new LinkedList<'key * 'value>()
fun (key : 'key) -> (
let found, value = cache.TryGetValue key
match found with
|true ->
keys.Remove value
keys.AddFirst value |> ignore
(snd value.Value)
|false ->
let newValue = key,reader key
let node = keys.AddFirst newValue
cache.[key] <- node
if (keys.Count > max) then
let lastNode = keys.Last
cache.Remove (fst lastNode.Value) |> ignore
keys.RemoveLast() |> ignore
(snd newValue))
Creating XElements
Nothing amazing, but I keep getting caught out by the implicit conversion of XNames:
#r "System.Xml.Linq.dll"
open System.Xml.Linq
//No! ("type string not compatible with XName")
//let el = new XElement("MyElement", "text")
//better
let xn s = XName.op_Implicit s
let el = new XElement(xn "MyElement", "text")
//or even
let xEl s o = new XElement(xn s, o)
let el = xEl "MyElement" "text"
Pairwise and pairs
I always expect Seq.pairwise to give me [(1,2);(3;4)] and not [(1,2);(2,3);(3,4)]. Given that neither exist in List, and that I needed both, here's the code for future reference. I think they're tail recursive.
//converts to 'windowed tuples' ([1;2;3;4;5] -> [(1,2);(2,3);(3,4);(4,5)])
let pairwise lst =
let rec loop prev rem acc =
match rem with
| hd::tl -> loop hd tl ((prev,hd)::acc)
| _ -> List.rev acc
loop (List.head lst) (List.tail lst) []
//converts to 'paged tuples' ([1;2;3;4;5;6] -> [(1,2);(3,4);(5,6)])
let pairs lst =
let rec loop rem acc =
match rem with
| l::r::tl -> loop tl ((l,r)::acc)
| l::[] -> failwith "odd-numbered list"
| _ -> List.rev acc
loop lst []
Naive CSV reader (i.e., won't handle anything nasty)
(Using filereadlines and List.transpose from other answers here)
///Given a file path, returns a List of row lists
let ReadCSV =
filereadlines
>> Array.map ( fun line -> line.Split([|',';';'|]) |> List.ofArray )
>> Array.toList
///takes list of col ids and list of rows,
/// returns array of columns (in requested order)
let GetColumns cols rows =
//Create filter
let pick cols (row:list<'a>) = List.map (fun i -> row.[i]) cols
rows
|> transpose //change list of rows to list of columns
|> pick cols //pick out the columns we want
|> Array.ofList //an array output is easier to index for user
Example
"C:\MySampleCSV"
|> ReadCSV
|> List.tail //skip header line
|> GetColumns [0;3;1] //reorder columns as well, if needs be.
Date Range
simple but useful list of dates between fromDate and toDate
let getDateRange fromDate toDate =
let rec dates (fromDate:System.DateTime) (toDate:System.DateTime) =
seq {
if fromDate <= toDate then
yield fromDate
yield! dates (fromDate.AddDays(1.0)) toDate
}
dates fromDate toDate
|> List.ofSeq
toggle code to sql
More trivial than most on this list, but handy nonetheless:
I'm always taking sql in and out of code to move it to a sql environment during development. Example:
let sql = "select a,b,c "
+ "from table "
+ "where a = 1"
needs to be 'stripped' to:
select a,b,c
from table
where a = 1
keeping the formatting. It's a pain to strip out the code symbols for the sql editor, then put them back again by hand when I've got the sql worked out. These two functions toggle the sql back and forth from code to stripped:
// reads the file with the code quoted sql, strips code symbols, dumps to FSI
let stripForSql fileName =
File.ReadAllText(fileName)
|> (fun s -> Regex.Replace(s, "\+(\s*)\"", ""))
|> (fun s -> s.Replace("\"", ""))
|> (fun s -> Regex.Replace(s, ";$", "")) // end of line semicolons
|> (fun s -> Regex.Replace(s, "//.+", "")) // get rid of any comments
|> (fun s -> printfn "%s" s)
then when you are ready to put it back into your code source file:
let prepFromSql fileName =
File.ReadAllText(fileName)
|> (fun s -> Regex.Replace(s, #"\r\n", " \"\r\n+\"")) // matches newline
|> (fun s -> Regex.Replace(s, #"\A", " \""))
|> (fun s -> Regex.Replace(s, #"\z", " \""))
|> (fun s -> printfn "%s" s)
I'd love to get rid of the input file but can't even begin to grok how to make that happen. anyone?
edit:
I figured out how to eliminate the requirement of a file for these functions by adding a windows forms dialog input/output. Too much code to show, but for those who would like to do such a thing, that's how I solved it.
Pascal's Triangle (hey, someone might find it useful)
So we want to create a something like this:
1
1 1
1 2 1
1 3 3 1
1 4 6 4 1
Easy enough:
let rec next = function
| [] -> []
| x::y::xs -> (x + y)::next (y::xs)
| x::xs -> x::next xs
let pascal n =
seq { 1 .. n }
|> List.scan (fun acc _ -> next (0::acc) ) [1]
The next function returns a new list where each item[i] = item[i] + item[i + 1].
Here's the output in fsi:
> pascal 10 |> Seq.iter (printfn "%A");;
[1]
[1; 1]
[1; 2; 1]
[1; 3; 3; 1]
[1; 4; 6; 4; 1]
[1; 5; 10; 10; 5; 1]
[1; 6; 15; 20; 15; 6; 1]
[1; 7; 21; 35; 35; 21; 7; 1]
[1; 8; 28; 56; 70; 56; 28; 8; 1]
[1; 9; 36; 84; 126; 126; 84; 36; 9; 1]
[1; 10; 45; 120; 210; 252; 210; 120; 45; 10; 1]
For the adventurous, here's a tail-recursive version:
let rec next2 cont = function
| [] -> cont []
| x::y::xs -> next2 (fun l -> cont <| (x + y)::l ) <| y::xs
| x::xs -> next2 (fun l -> cont <| x::l ) <| xs
let pascal2 n =
set { 1 .. n }
|> Seq.scan (fun acc _ -> next2 id <| 0::acc)) [1]
Flatten a List
if you have something like this:
let listList = [[1;2;3;];[4;5;6]]
and want to 'flatten' it down to a singe list so the result is like this:
[1;2;3;4;5;6]
it can be done thusly:
let flatten (l: 'a list list) =
seq {
yield List.head (List.head l)
for a in l do yield! (Seq.skip 1 a)
}
|> List.ofSeq
List comprehensions for float
This [23.0 .. 1.0 .. 40.0] was marked as deprecated a few versions backed.
But apparently, this works:
let dl = 9.5 / 11.
let min = 21.5 + dl
let max = 40.5 - dl
let a = [ for z in min .. dl .. max -> z ]
let b = a.Length
(BTW, there's a floating point gotcha in there. Discovered at fssnip - the other place for F# snippets)
Parallel map
let pmap f s =
seq { for a in s -> async { return f s } }
|> Async.Parallel
|> Async.Run

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