In the F# core libraries there are functions whose signature seemingly changes based on the parameter at compile-time:
> sprintf "Hello %i" ;;
val it : (int -> string) = <fun:it#1>
> sprintf "Hello %s" ;;
val it : (string -> string) = <fun:it#2-1>
Is it possible to implement my own functions that have this property?
For example, could I design a function that matches strings with variable components:
matchPath "/products/:string/:string" (fun (category : string) (sku : string) -> ())
matchPath "/tickets/:int" (fun (id : int) -> ())
Ideally, I would like to do avoid dynamic casts.
There are two relevant F# features that make it possible to do something like this.
Printf format strings. The compiler handles format strings like "hi %s" in a special way. They are not limited just to printf and it's possible to use those in your library in a somewhat different way. This does not let you change the syntax, but if you were happy to specify your paths using e.g. "/products/%s/%d", then you could use this. The Giraffe library defines routef function, which uses this trick for request routing:
let webApp =
choose [
routef "/foo/%s/%s/%i" fooHandler
routef "/bar/%O" (fun guid -> text (guid.ToString()))
]
Type providers. Another option is to use F# type providers. With parameterized type providers, you can write a type that is parameterized by a literal string and has members with types that are generated by some F# code you write based on the literal string parameter. An example is the Regex type provider:
type TempRegex = Regex< #"^(?<Temperature>[\d\.]+)\s*°C$", noMethodPrefix = true >
TempRegex().Match("21.3°C").Temperature.TryValue
Here, the regular expression on the first line is static parameter of the Regex type provider. The type provider generates a Match method which returns an object with properties like Temperature that are based on the literal string. You would likely be able to use this and write something like:
MatchPath<"/products/:category/:sku">.Match(fun r ->
printfn "Got category %s and sku %s" r.Category r.Sku)
I tweaked your example so that r is an object with properties that have names matching to those in the string, but you could use a lambda with multiple parameters too. Although, if you wanted to specify types of those matches, you might need a fancier syntax like "/product/[category:int]/[sku:string]" - this is just a string you have to parse in the type provider, so it's completely up to you.
1st: Tomas's answer is the right answer.
But ... I had the same question.
And while I could understand it conceptually as "it has to be 'the string format thing' or 'the provider stuff'"
I could not tell my self that I got until I tried an implementation
... And it took me a bit .
I used FSharp.Core's printfs and Giraffe's FormatExpressions.fs as guidelines
And came up with this naive gist/implementation, inspired by Giraffe FormatExpressions.fs
BTW The trick is in this bit of magic fun (format: PrintfFormat<_, _, _, _, 'T>) (handle: 'T -> 'R)
open System.Text.RegularExpressions
// convert format pattern to Regex Pattern
let rec toRegexPattern =
function
| '%' :: c :: tail ->
match c with
| 'i' ->
let x, rest = toRegexPattern tail
"(\d+)" + x, rest
| 's' ->
let x, rest = toRegexPattern tail
"(\w+)" + x, rest
| x ->
failwithf "'%%%c' is Not Implemented\n" x
| c :: tail ->
let x, rest = toRegexPattern tail
let r = c.ToString() |> Regex.Escape
r + x, rest
| [] -> "", []
// Handler Factory
let inline Handler (format: PrintfFormat<_, _, _, _, 'T>) (handle: 'T -> string) (decode: string list -> 'T) =
format.Value.ToCharArray()
|> List.ofArray
|> toRegexPattern
|> fst, handle, decode
// Active Patterns
let (|RegexMatch|_|) pattern input =
let m = Regex.Match(input, pattern)
if m.Success then
let values =
[ for g in Regex(pattern).Match(input).Groups do
if g.Success && g.Name <> "0" then yield g.Value ]
Some values
else
None
let getPattern (pattern, _, _) = pattern
let gethandler (_, handle, _) = handle
let getDecoder (_, _, decode) = decode
let Router path =
let route1 =
Handler "/xyz/%s/%i"
(fun (category, id) ->
// process request
sprintf "handled: route1: %s/%i" category id)
(fun values ->
// convert matches
values |> List.item 0,
values
|> List.item 1
|> int32)
let route2 =
Handler "/xyz/%i"
(fun (id) -> sprintf "handled: route2: id: %i" id) // handle
(fun values -> values|> List.head |> int32) // decode
// Router
(match path with
| RegexMatch (getPattern route2) values ->
values
|> getDecoder route2
|> gethandler route2
| RegexMatch (getPattern route1) values ->
values
|> getDecoder route1
|> gethandler route1
| _ -> failwith "No Match")
|> printf "routed: %A\n"
let main argv =
try
let arg = argv |> Array.skip 1 |> Array.head
Router arg
0 // return an integer exit code
with
| Failure msg ->
eprintf "Error: %s\n" msg
-1
I would like to consolidate the following lines:
let result1 = add (numbers, ",")
let result2 = add (numbers, "\n")
into something like this:
let resultX = add (numbers, ",") |> add (numbers, "\n")
Can I compose functions like this?
NOTE:
I am learning F# and apologize if this question seems silly.
The code is below:
module Calculator
open FsUnit
open NUnit.Framework
open System
let add (numbers:string) =
let add (numbers:string) (delimiter:string) =
if (numbers.Contains(delimiter)) then
numbers.Split(delimiter.Chars(0)) |> Array.map Int32.Parse
|> Array.sum
else 0
let result1 = add numbers ","
let result2 = add numbers "\n"
if (result1 > 0 || result2 > 0) then
result1 + result2
else let _ , result = numbers |> Int32.TryParse
result
Tests:
[<Test>]
let ``adding empty string returns zero`` () =
let result = add ""
result |> should equal 0
[<Test>]
let ``adding one number returns number`` () =
let result = add "3"
result |> should equal 3
[<Test>]
let ``add two numbers`` () =
let result = add "3,4"
result |> should equal 7
[<Test>]
let ``add three numbers`` () =
let result = add "3,4,5"
result |> should equal 12
[<Test>]
let ``line feeds embedded`` () =
let result = add "3\n4"
result |> should equal 7
UPDATED
I receive the following error:
The type 'int' does not match the type 'string'
let add (numbers:string) =
let add (numbers:string) (delimiter:string) =
if (numbers.Contains(delimiter)) then
numbers.Split(delimiter.Chars(0)) |> Array.map Int32.Parse
|> Array.sum
else 0
let resultX = numbers |> add ","
|> add "\n"
Implemented Feedback:
let add (numbers:string) =
let add (numbers:string) (delimiters:char array) =
if numbers.Length = 0 then 0
else numbers.Split(delimiters) |> Array.map Int32.Parse
|> Array.sum
let delimiters = [|',';'\n'|]
add numbers delimiters
This is not an exact answer as I am not sure what you mean but it should give you some ideas.
let add01 (numbers:string) =
let delimiters : char array = [|',';'\n'|]
let inputArray : string array = numbers.Split(delimiters)
let numbers : string list = Array.toList(inputArray)
let rec add (numbers : string list) (total : int) : int =
match (numbers : string list) with
| ""::t ->
add t total
| h::t ->
let number = System.Int32.Parse h
let total = total + number
add t total
| [] -> total
add numbers 0
let numbers = "1,2,3\n4,5,6\n\n"
let result = add01 numbers
When given the following code the following error occurs, why?
// Type mismatch. Expecting a
// int -> 'a
// but given a
// string -> int
// The type 'int' does not match the type 'string'
let result = numbers |> add ","
|> add "\n"
Since this is an error stating that two types do not agree one needs to understand type inferencing and how to resolve such problems.
I will not explain type inferencing here as that is a large topic in itself, however I will give an example of a pattern that works successfully most of time for me in resolving such errors.
When F# compiles code it uses type inferencing to add the missing types to functions and values before doing a type check and it is the type check that is failing. So to see what the compiler sees for the types we will manually add them here and factor out the parts of the code that are not causing a problem leaving us with the cause of the error hopefully in something then becomes obvious to fix.
The only things that have types are:
result
=
numbers
|>
add
","
"\n"
The types for the values are easy:
result : int
numbers : string
"," : string
"\n" : string
I don't recall F# treating equals (=) as a function but here is how to think of it.
= : 'a -> 'a
The pipeline operator
let (|>) (x : 'a) f = f (x : 'a)
For resolving the problem just think of the pipeline operator as syntactic sugar.
See examples below for better understanding.
The add function
add : string -> string -> int
So lets refine the error down to its essence.
//Type mismatch. Expecting a
// int -> 'a
//but given a
// string -> int
//The type 'int' does not match the type 'string'
let result = numbers |> add ","
|> add "\n"
Add the type signatures to the values and verify we get the same error.
This is what type inferencing would do and we did it manually.
//Type mismatch. Expecting a
// int -> int
//but given a
// string -> int
//The type 'int' does not match the type 'string'
let (result : int) = (numbers : string) |> add ("," : string)
|> add ("\n" : string)
Now think of the code as a mathematical expression which can be factored.
Factor out the first pipeline operator and verify we get the same error.
Notice the error is now only part of r2
//Expecting a
// int -> 'a
//but given a
// string -> int
//The type 'int' does not match the type 'string'
let (result : int) =
let r1 = (numbers : string) |> add ("," : string)
let r2 = r1 |> add ("\n" : string)
r2
Undo the syntactic sugar for the second pipeline operator and verify we get the same error.
Notice the error is now only part of r2; specifically the r1 argument
//This expression was expected to have type
// string
//but here has type
// int
let (result : int) =
let r1 = (numbers : string) |> add ("," : string)
let r2 = add ("\n" : string) r1
r2
Add the type to r1 and verify we get the same error.
//This expression was expected to have type
// string
//but here has type
// int
let (result : int) =
let (r1 : int) = (numbers : string) |> add ("," : string)
let r2 = add ("\n" : string) r1
r2
At this point the error should be obvious.
The result of the first pipeline operator is an int and is passed to the add function as the second argument.
The add function expects a string for the second argument but was given an int.
To better understand how the pipeline operator works I created an equivalent user defined operator for this demonstration.
These are some helper functions for the demonstration.
let output1 w =
printfn "1: %A" w
let output2 w x =
printfn "1: %A 2: %A" w x
let output3 w x y =
printfn "1: %A 2: %A 3: %A" w x y
let output4 w x y z =
printfn "1: %A 2: %A 3: %A 4: %A" w x y z
Using the output functions without the pipeline operator.
output1 "a"
1: "a"
output2 "a" "b"
1: "a" 2: "b"
output3 "a" "b" "c"
1: "a" 2: "b" 3: "c"
output4 "a" "b" "c" "d"
1: "a" 2: "b" 3: "c" 4: "d"
Notice that the output is in the same order as the input.
Using the output functions with the pipeline operator.
// let (|>) x f = fx
"a" |> output1
1: "a"
"a" |> output2 "b"
1: "b" 2: "a"
"a" |> output3 "b" "c"
1: "b" 2: "c" 3: "a"
"a" |> output4 "b" "c" "d"
1: "b" 2: "c" 3: "d" 4: "a"
NOTICE that the last argument for the output functions is the value on the left of the pipeline operator ("a") because of the use of the pipeline operator (|>).
// See section 3.7 of the F# specification on how to define user defined operators.
Using the output functions with the user defined pipeline operator.
let (#.) x f = f x
"a" #. output1
1: "a"
"a" #. output2 "b"
1: "b" 2: "a"
"a" #. output3 "b" "c"
1: "b" 2: "c" 3: "a"
"a" #. output4 "b" "c" "d"
1: "b" 2: "c" 3: "d" 4: "a"
I'm not aware of any universal way to compose functions like you seem to be asking, but if you only need to vary one argument, one option is to create a list of arguments, and then map over those:
let results = [","; "\n"] |> List.map (add numbers)
If you do this, then results is an int list, and then you need to decide what to do with that list. In this case, it would seem appropriate to sum over the list, but given the current conditionals that check if result1 or result2 are positive, that doesn't seem appropriate.
All that said, given the current test cases supplied, there's no reason to make it more complicated than it has to be. This implementation also passes all the tests:
let add =
let split (x : string) =
x.Split([| ','; '\n' |], StringSplitOptions.RemoveEmptyEntries)
split >> Array.map Int32.Parse >> Array.sum
This isn't a particularly robust implementation, as it'll fail if the string contains characters that can't be parsed into integers, but so will the OP implementation.
I'm just starting up with F# and see how you can use currying to pre-load the 1st parameter to a function. But how would one do it with the 2nd, 3rd, or whatever other parameter? Would named parameters to make this easier? Are there any other functional languages that have named parameters or some other way to make currying indifferent to parameter-order?
Typically you just use a lambda:
fun x y z -> f x y 42
is a function like 'f' but with the third parameter bound to 42.
You can also use combinators (like someone mentioned Haskell's "flip" in a comment), which reorder arguments, but I sometimes find that confusing.
Note that most curried functions are written so that the argument-most-likely-to-be-partially-applied comes first.
F# has named parameters for methods (not let-bound function values), but the names apply to 'tupled' parameters. Named curried parameters do not make much sense; if I have a two-argument curried function 'f', I would expect that given
let g = f
let h x y = f x y
then 'g' or 'h' would be substitutable for 'f', but 'named' parameters make this not necessarily true. That is to say, 'named parameters' can interact poorly with other aspects of the language design, and I personally don't know of a good design offhand for 'named parameters' that interacts well with 'first class curried function values'.
OCaml, the language that F# was based on, has labeled (and optional) arguments that can be specified in any order, and you can partially apply a function based on those arguments' names. I don't believe F# has this feature.
You might try creating something like Haskell's flip function. Creating variants that jump the argument further in the argument list shouldn't be too hard.
let flip f a b = f b a
let flip2 f a b c = f b c a
let flip3 f a b c d = f b c d a
Just for completeness - and since you asked about other functional languages - this is how you would do it in OCaml, arguably the "mother" of F#:
$ ocaml
# let foo ~x ~y = x - y ;;
val foo : x:int -> y:int -> int = <fun>
# foo 5 3;;
- : int = 2
# let bar = foo ~y:3;;
val bar : x:int -> int = <fun>
# bar 5;;
- : int = 2
So in OCaml you can hardcode any named parameter you want, just by using its name (y in the example above).
Microsoft chose not to implement this feature, as you found out... In my humble opinion, it's not about "poor interaction with other aspects of the language design"... it is more likely because of the additional effort this would require (in the language implementation) and the delay it would cause in bringing the language to the world - when in fact only few people would (a) be aware of the "stepdown" from OCaml, (b) use named function arguments anyway.
I am in the minority, and do use them - but it is indeed something easily emulated in F# with a local function binding:
let foo x y = x - y
let bar x = foo x 3
bar ...
It's possible to do this without declaring anything, but I agree with Brian that a lambda or a custom function is probably a better solution.
I find that I most frequently want this for partial application of division or subtraction.
> let halve = (/) >> (|>) 2.0;;
> let halfPi = halve System.Math.PI;;
val halve : (float -> float)
val halfPi : float = 1.570796327
To generalize, we can declare a function applySecond:
> let applySecond f arg2 = f >> (|>) arg2;;
val applySecond : f:('a -> 'b -> 'c) -> arg2:'b -> ('a -> 'c)
To follow the logic, it might help to define the function thus:
> let applySecond f arg2 =
- let ff = (|>) arg2
- f >> ff;;
val applySecond : f:('a -> 'b -> 'c) -> arg2:'b -> ('a -> 'c)
Now f is a function from 'a to 'b -> 'c. This is composed with ff, a function from 'b -> 'c to 'c that results from the partial application of arg2 to the forward pipeline operator. This function applies the specific 'b value passed for arg2 to its argument. So when we compose f with ff, we get a function from 'a to 'c that uses the given value for the 'b argument, which is just what we wanted.
Compare the first example above to the following:
> let halve f = f / 2.0;;
> let halfPi = halve System.Math.PI;;
val halve : f:float -> float
val halfPi : float = 1.570796327
Also compare these:
let filterTwoDigitInts = List.filter >> (|>) [10 .. 99]
let oddTwoDigitInts = filterTwoDigitInts ((&&&) 1 >> (=) 1)
let evenTwoDigitInts = filterTwoDigitInts ((&&&) 1 >> (=) 0)
let filterTwoDigitInts f = List.filter f [10 .. 99]
let oddTwoDigitInts = filterTwoDigitInts (fun i -> i &&& 1 = 1)
let evenTwoDigitInts = filterTwoDigitInts (fun i -> i &&& 1 = 0)
Alternatively, compare:
let someFloats = [0.0 .. 10.0]
let theFloatsDividedByFour1 = someFloats |> List.map ((/) >> (|>) 4.0)
let theFloatsDividedByFour2 = someFloats |> List.map (fun f -> f / 4.0)
The lambda versions seem to be easier to read.
In Python, you can use functools.partial, or a lambda. Python has named arguments.
functools.partial can be used to specify the first positional arguments as well as any named argument.
from functools import partial
def foo(a, b, bar=None):
...
f = partial(foo, bar='wzzz') # f(1, 2) ~ foo(1, 2, bar='wzzz')
f2 = partial(foo, 3) # f2(5) ~ foo(3, 5)
f3 = lambda a: foo(a, 7) # f3(9) ~ foo(9, 7)
As it currently stands, this question is not a good fit for our Q&A format. We expect answers to be supported by facts, references, or expertise, but this question will likely solicit debate, arguments, polling, or extended discussion. If you feel that this question can be improved and possibly reopened, visit the help center for guidance.
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