I'm learning F# and I am building a quick set of functions which compare two poker hands and determine the winner.
I made this discriminated union to represent categories of poker hands:
type Category =
| HighCard
| OnePair
| TwoPair
| ThreeOfAKind
| Straight
| Flush
| FullHouse
| FourOfAKind
| StraightFlush
I use this code to compare categories to determine if one hand is better than another:
if playerCategory > houseCategory then Win
elif playerCategory < houseCategory then Loss
// ... More code to handle cases within the same category
So, for example, the expression:
let playerCategory = FullHouse
let houseCategory = HighCard
if playerCategory > houseCategory then Win
elif playerCategory < houseCategory then Loss
// ... Other code
Would have the value Win.
However, I don't understand how the < and > operators are able to work here. (Originally I had a function which mapped each case to a numeric value, but I realized it wasn't necessary.) If I rearrange the order of the cases then the logic breaks, so I'm assuming each case is assigned some default value corresponding to its order within the type?
But I would definitely appreciate a bit more insight...
This is described in the specification:
by default, record, union, and struct type definitions called
structural types implicitly include compiler-generated declarations
for structural equality, hashing, and comparison. These implicit
declarations consist of the following for structural equality and
hashing
8.15.4 Behavior of the Generated CompareTo implementations
If T is a union type, invoke Microsoft.FSharp.Core.Operators.compare
first on the index of the union cases for the two values, and then on
each corresponding field pair of x and y for the data carried by the
union case. Return the first non-zero result.
In addition to what Lee said, there's also in the spec
8.5.4 Compiled Form of Union Types for Use from Other CLI Languages
A compiled union type U has:
...
One CLI instance property U.Tag for each case C. This property fetches or computes an integer tag corresponding to the case.
The compiler-generated CompareTo method uses the backing fields of these properties to determine the index as stipulated in 8.15.4. This is evidenced by IlSpy:
int tag = this._tag;
int tag2 = category._tag;
if (tag != tag2)
{
return tag - tag2;
}
if (this.Tag != 0)
{
return 0;
}
Related
I've been reading F# articles and they use single case variants to create distinct incompatible types. However in Ocaml I can use private module types or abstract types to create distinct types. Is it common in Ocaml to use single case variants like in F# or Haskell?
Another specialized use case fo a single constructor variant is to erase some type information with a GADT (and an existential quantification).
For instance, in
type showable = Show: 'a * ('a -> string) -> showable
let show (Show (x,f)) = f x
let showables = [ Show (0,string_of_int); Show("string", Fun.id) ]
The constructor Show pairs an element of a given type with a printing function, then forget the concrete type of the element. This makes it possible to have a list of showable elements, even if each elements had a different concrete types.
For what it's worth it seems to me this wasn't particularly common in OCaml in the past.
I've been reluctant to do this myself because it has always cost something: the representation of type t = T of int was always bigger than just the representation of an int.
However recently (probably a few years) it's possible to declare types as unboxed, which removes this obstacle:
type [#unboxed] t = T of int
As a result I've personally been using single-constructor types much more frequently recently. There are many advantages. For me the main one is that I can have a distinct type that's independent of whether it's representation happens to be the same as another type.
You can of course use modules to get this effect, as you say. But that is a fairly heavy solution.
(All of this is just my opinion naturally.)
Yet another case for single-constructor types (although it does not quite match your initial question of creating distinct types): fancy records. (By contrast with other answers, this is more a syntactic convenience than a fundamental feature.)
Indeed, using a relatively recent feature (introduced with OCaml 4.03, in 2016) which allows writing constructor arguments with a record syntax (including mutable fields!), you can prefix regular records with a constructor name, Coq-style.
type t = MakeT of {
mutable x : int ;
mutable y : string ;
}
let some_t = MakeT { x = 4 ; y = "tea" }
(* val some_t : t = MakeT {x = 4; y = "tea"} *)
It does not change anything at runtime (just like Constr (a,b) has the same representation as (a,b), provided Constr is the only constructor of its type). The constructor makes the code a bit more explicit to the human eye, and it also provides the type information required to disambiguate field names, thus avoiding the need for type annotations. It is similar in function to the usual module trick, but more systematic.
Patterns work just the same:
let (MakeT { x ; y }) = some_t
(* val x : int = 4 *)
(* val y : string = "tea" *)
You can also access the “contained” record (at no runtime cost), read and modify its fields. This contained record however is not a first-class value: you cannot store it, pass it to a function nor return it.
let (MakeT fields) = some_t in fields.x (* returns 4 *)
let (MakeT fields) = some_t in fields.x <- 42
(* some_t is now MakeT {x = 42; y = "tea"} *)
let (MakeT fields) = some_t in fields
(* ^^^^^^
Error: This form is not allowed as the type of the inlined record could escape. *)
Another use case of single-constructor (polymorphic) variants is documenting something to the caller of a function. For instance, perhaps there's a caveat with the value that your function returns:
val create : unit -> [ `Must_call_close of t ]
Using a variant forces the caller of your function to pattern-match on this variant in their code:
let (`Must_call_close t) = create () in (* ... *)
This makes it more likely that they'll pay attention to the message in the variant, as opposed to documentation in an .mli file that could get missed.
For this use case, polymorphic variants are a bit easier to work with as you don't need to define an intermediate type for the variant.
I am trying to understand the following code, particularly StringConstant:
type StringConstant = StringConstant of string * string
[<EntryPoint>]
let main argv =
let x = StringConstant("little", "shack")
printfn "%A" x
0 // return an integer exit code
(By way of context, StringConstant is used in the FParsec tutorial, but this example does not use FParsec.)
What I would like to know is:
what exactly is the type statement doing?
once I instantiate x, how would I access the individual "parts"
("little" or "house")
As others already noted, technically, StringConstant is a discriminated union with just a single case and you can extract the value using pattern matching.
When talking about domain modelling in F#, I like to use another useful analogy. Often, you can start just by saying that some data type is a tuple:
type Person = string * int
This is really easy way to represent data, but the problem is that when you write "Tomas", 42, the compiler does not know that you mean Person, but instead understands it as string * int tuple. One-case discriminated unions are a really nice way to name your tuple:
type Person = Person of string * int
It might be a bit confusing that this is using the name Person twice - first as a type name and second as a name of the case. This has no special meaning - it simply means that the type will have the same name as the case.
Now you can write Person("Tomas", 42) to create a value and it will have a type Person. You can decompose it using match or let, but you can also easily write functions that take Person. For example, to return name, you can write:
let getName (Person(name, _)) =
name
I think single-case discriminated unions are often used mainly because they are really easy to define and really easy to work with. However, I would not use them in code that is exposed as a public API because they are a bit unusual and may be confusing.
PS: Also note that you need to use parentheses when extracting the values:
// Correct. Defines symbols 'name' and 'age'
let (Person(name, age)) = tomas
// Incorrect! Defines a function `Person` that takes a tuple
// (and hides the `Person` case of the discriminated union)
let Person(name, age) = tomas
StringConstant is a discriminated union type, with just a single case (also named StringConstant). You extract the parts via pattern matching, using match/function or even just let, since there is just a single case:
let (StringConstant(firstPart, secondPart)) = x
type StringConstant = StringConstant of string * string
results in a discriminated union with one type.
type StringConstant = | StringConstant of string * string if you execute it in F# interactive.
You can see the msdn documentation on that here.
You can get the value out like this:
let printValue opt =
match opt with
| StringConstant( x, y) -> printfn "%A%A" x y
The other guys already mentioned how you extract the data from a discriminated union, but to elaborate a little more on Discriminated unions one could say that they are sorta like enums on steroids. They are implemented behind the scenes as a type hierarchy where the type is the base class and the cases are subclases of that baseclass with whatever parameter they might have as readonly public variables.
In Scala a similar data-structure is called case classes which might help you convince yourself of this implementationmethod.
One nice property of discriminated unions are that they are self-referenceable and therefor are perfect for defining recursive structures like a tree. Below is a definition of a Hoffman coding tree in just three lines of code. Doing that in C# would probably take somewhere between 5 and 10 times as many lines of code.
type CodeTree =
| Branch of CodeTree * CodeTree * list<char> * int
| Leaf of char * int
For information about Discriminated Unions see the msdn documentation
For an example of using Discriminated Unions as a tree-structure see this gist which is an implementation of a huffman decoder in roughly 60 lines of F#)
I'm new in F#.
How do I check whether a variable is an integer or another type.
Thanks.
One way is listed by #ildjarn in the comments:
let isInt x = box x :? int
An idiomatic way would be to use pattern matching. First, define a discriminated union which defines the possible options:
type Test =
| IsAnInteger of int
| IsADouble of double
| NotANumber of Object
then use a match statement to determine which option you got. Note that when you initially create the value you wish to use with a match statement, you need to put it into the discriminated union type.
let GetValue x =
match x with
| IsAnInteger(a) -> a
| IsADouble(b) -> (int)b
| NotAnInteger(_) -> 0
Since you're probably going to use your test to determine control flow, you might as well do it idiomatically. This can also prevent you from missing cases since match statements give you warnings if you don't handle all possible cases.
>GetValue (NotAnInteger("test"));;
val it : int = 0
>GetValue (IsADouble(3.3))
val it : int = 3
>GetValue (IsAnInteger(5))
val it : int = 5
Considering that you tagged this question "c#-to-f#" I'm assuming you're coming to F# from a C# background. Therefore I think you may be a bit confused by the type inference since you're probably used to explicitly typing variables.
You can explicitly declare the type of a value if you need to.
let x:int = 3
But it's usually easier and better to let the type inference do this work for you. You'll note that I said value--the declaration above is not a variable because you cannot do a destructive assignment to it. If you want a variable then do this:
let mutable x:int = 3
You can then assign a new value to x via this construct
x <- 5
But, as a rule, you'll want to avoid mutable values.
CompilationRepresentationFlags.UseNullAsTrueValue can be used to
Permit the use of null as a representation for nullary discriminators in a discriminated union
Option.None is the most prominent example of this.
Why is this useful? How is a null check better than the traditional mechanism for checking union cases (the generated Tag property)?
It leads to perhaps unexpected behavior:
Some(1).ToString() //"Some(1)"
None.ToString() //NullReferenceException
EDIT
I tested Jack's assertion that comparing to null instead of a static readonly field is faster.
[<CompilationRepresentation(CompilationRepresentationFlags.UseNullAsTrueValue)>]
type T<'T> =
| Z
| X of 'T
let t = Z
Using ILSpy, I can see t compiles to null (as expected):
public static Test.T<a> t<a>()
{
return null;
}
The test:
let mutable i = 0
for _ in 1 .. 10000000 do
match t with
| Z -> i <- i + 1
| _ -> ()
The results:
Real: 00:00:00.036, CPU: 00:00:00.046, GC gen0: 0, gen1: 0, gen2: 0
If the CompilationRepresentation attribute is removed, t becomes a static readonly field:
public static Test.T<a> t<a>()
{
return Test.T<a>.Z;
}
public static Test.T<T> Z
{
[CompilationMapping(SourceConstructFlags.UnionCase, 0)]
get
{
return Test.T<T>._unique_Z;
}
}
internal static readonly Test.T<T> _unique_Z = new Test.T<T>._Z();
And the results are the same:
Real: 00:00:00.036, CPU: 00:00:00.031, GC gen0: 0, gen1: 0, gen2: 0
The pattern match is compiled as t == null in the former case and t is Z in the latter.
The F# compiler sometimes uses null as a representation for None because it's more efficient than actually creating an instance of FSharpOption<'T> and checking the Tag property.
Think about it -- if you have a normal F# type (like a record) that's not allowed to be null, then any pointer to an instance of that type (the pointer used internally by the CLR) will never be NULL. At the same time, if T is a type which can represent n states, then T option can represent n+1 states. So, using null as a representation for None simply takes advantage of that one extra state value which is available by the fact that F# types aren't allow to be null.
If you want to try turning this behavior off (for normal F# types), you can apply [<AllowNullLiteral(true)>] to them.
Jack's answer seems good, but to expand a little bit, at the IL level the CLR provides a specific opcode for loading null values (ldnull) and efficient means of testing for them (ldnull followed by beq/bne.un/ceq/cgt.un). When JITted, these should be more efficient than dereferencing a Tag property and branching accordingly. While the per-call savings are probably small, option types are used frequently enough that the cumulative savings may be significant.
Of course, as you note there is a tradeoff: methods inherited from obj may throw null reference exceptions. This is one good reason to use string x/hash x/x=y instead of x.ToString()/x.GetHashCode()/x.Equals(y) when dealing with F# values. Sadly, there is no (possible) equivalent of x.GetType() for values represented by null.
I am trying to design an AST for a decision logic table. One of the things I would like to be able to do with the discriminated union that represents my AST is transform parts of it for different reasons. For clarity I will give you an example
Decision Logic Table
# VAR = 10 ;Y;
The above can be read as there is one rule and the condition VAR = 10 enters this rule with a Y entry.
Abstract Syntax Tree Definition (simplified for this example)
type expression =
| Value of double
| Variable of string
| Equality of expression * expression
type entry =
| Entry of string
type entries =
| Entries of entry list
type conditional =
| ConditionEntries of expression * entries
type condition
| Condition of expression * string
type rule =
| Rule of condition list
Rendered (before transform)
ConditionEntries(
Equality(
Variable("VAR"),
Value(10.0)),
Entries(["Y"]))
Rendered (after transform)
Rule(
Condition(
Equality(
Variable("VAR"),
Value(10.0)
),
Entry("Y")
)
)
Now what I would like to do is transform the above tree to expand the rules that are represented in the entries. My thinking was I could use a recursive function and pattern-matching to do this but I am having a little trouble wrapping my head around it right now.
I guess in essence what I am trying to do is whenever I see a ConditionEntries node, I want to emit a new Rule for every string in the Entries list where the Condition is combined with the Entry. Does that make any sense?
Thanks in advance for any advice.
p.s. I haven't quite tried to compile the above example, so please forgive any grammatical errors.
Hmm, based on your AST, which is awfully broken up, here is a tranform function which produces the output from input you desire (though it's not recursive, just uses List.map with some pattern matching. expression is your only recursive type but it doesn't look like you want to process it recursively?):
let ex1 =
ConditionEntries(
Equality(
Variable("VAR"),
Value(10.0)),
Entries([Entry("Y")]))
let ex2 =
ConditionEntries(
Equality(
Variable("VAR"),
Value(10.0)),
Entries([Entry("X");Entry("Y");Entry("Z")]))
let transform ces =
match ces with
| ConditionEntries(x, Entries(entries)) ->
entries
|> List.map (function Entry(entry) -> Condition(x, entry))
//FSI output:
> transform ex1;;
val it : condition list =
[Condition (Equality (Variable "VAR",Value 10.0),"Y")]
> transform ex2;;
val it : condition list =
[Condition (Equality (Variable "VAR",Value 10.0),"X");
Condition (Equality (Variable "VAR",Value 10.0),"Y");
Condition (Equality (Variable "VAR",Value 10.0),"Z")]