Difference between f(s::String) and f(::String) - syntax

What is the difference between the following two functions?
julia> one(s::String) = return 1
one (generic function with 1 method)
julia> one(::String) = return 1
one (generic function with 1 method)
Both seem to be allowed and there doesn't seem to be a difference between them. I suppose not including the v could signal to the compiler that the value of the argument is not used, but then again this is something the compiler can figure out, right? (Disclaimer: I have no idea how compilers work)

There is no difference if you don't use the argument, and yes, for the compiler this should be trivial.
You can use _ as an actual "discard argument" though, and the parser will prevent you from using it:
julia> f(_) = _ + 1
ERROR: syntax: all-underscore identifier used as rvalue around REPL[9]:1
That's useful in some situations:
julia> _, _, z = (1,2,3)
(1, 2, 3)
julia> z
3
julia> _
ERROR: all-underscore identifier used as rvalue
while
julia> x, x, z = (1,2,3)
(1, 2, 3)
julia> x
2
is slightly confusing.
More technicalities
An unused argument is preseved in IR, though:
julia> one(::String) = return 1
one (generic function with 1 method)
julia> one2(s::String) = return 1
one2 (generic function with 1 method)
julia> ir = #code_lowered one("sdf")
CodeInfo(
1 ─ return 1
)
julia> ir.slotnames
2-element Array{Symbol,1}:
Symbol("#self#")
Symbol("#unused#")
julia> ir2 = #code_lowered one2("sdf")
CodeInfo(
1 ─ return 1
)
julia> ir2.slotnames
2-element Array{Symbol,1}:
Symbol("#self#")
:s
If you ever care about slot names. I can't imagine how this would change further compilation, but it can be a corner case in metaprogramming.

Related

Allow outer variable inside Julia's sort comparison

The issue:
I want to be able to sort with a custom function that depends on an outer defined variable, for example:
k = 2
sort([1,2,3], lt=(x,y) -> x + k > y)
This works all dandy and such because k is defined in the global scope.
That's where my issue lays, as I want to do something akin to:
function
k = 2
comp = (x,y) -> x + k > y
sort([1,3,3], lt=comp)
end
Which works, but feels like a hack, because my comparison function is way bigger and it feels really off to have to have it defined there in the body of the function.
For instance, this wouldn't work:
comp = (x,y) -> x + k > y # or function comp(x,y) ... end
function
k = 2
sort([1,3,3], lt=comp)
end
So I'm just wondering if there's any way to capture variables such as k like you'd be able to do with lambda functions in C++.
Is this what you want?
julia> comp(k) = (x,y) -> x + k > y
comp (generic function with 1 method)
julia> sort([1,3,2,3,2,2,2,3], lt=comp(2))
8-element Vector{Int64}:
3
2
2
2
3
2
3
1

Retrieve method content as an `Expr`ession

I have a function f defined as follows.
f(x, y) = 3x^2 + x*y - 2y + 1
How can I retrieve the following quote block for this method, which includes the function contents?
quote # REPL[0], line 2:
((3 * x ^ 2 + x * y) - 2y) + 1
end
As folks have mentioned in the comments, digging through the fields of the methods like this isn't a stable or officially supported API. Further, your simple example is deceiving. This isn't, in general, representative of the original code you wrote for the method. It's a simplified intermediate AST representation with single-assignment variables and drastically simplified control flow. In general, the AST it returns isn't valid top-level Julia code. It just so happens that for your simple example, it is.
That said, there is a documented way to do this. You can use code_lowered() to get access to this intermediate representation without digging through undocumented fields. This will work across Julia versions, but I don't think there are official guarantees on the stability of the intermediate representation yet. Here's a slightly more complicated example:
julia> f(X) = for elt in X; println(elt); end
f (generic function with 1 method)
julia> code_lowered(f)[1]
LambdaInfo template for f(X) at REPL[17]:1
:(begin
nothing
SSAValue(0) = X
#temp# = (Base.start)(SSAValue(0))
4:
unless !((Base.done)(SSAValue(0),#temp#)) goto 13
SSAValue(1) = (Base.next)(SSAValue(0),#temp#)
elt = (Core.getfield)(SSAValue(1),1)
#temp# = (Core.getfield)(SSAValue(1),2) # line 1:
(Main.println)(elt)
11:
goto 4
13:
return
end)
julia> code_lowered(f)[1] == methods(f).ms[1].lambda_template
true
If you really want to see the code exactly as it was written, the best way is to use the embedded file and line information and refer to the original source. Note that this is precisely the manner in which Gallium.jl (Julia's debugger) finds the source to display as it steps through functions. It's undocumented, but you can even access the REPL history for functions defined interactively. See how Gallium does it through here.
First, retrieve the method using methods(f).
julia> methods(f)
# 1 method for generic function "f":
f(x, y) at REPL[1]:1
julia> methods(f).ms
1-element Array{Method,1}:
f(x, y) at REPL[1]:1
julia> method = methods(f).ms[1]
f(x, y) at REPL[1]:1
From here, retrieving the Expression is straightforward; simply use the lambda_template attribute of the method.
julia> method.lambda_template
LambdaInfo template for f(x, y) at REPL[1]:1
:(begin
nothing
return ((3 * x ^ 2 + x * y) - 2 * y) + 1
end)
Edit: This does not work in Julia v0.6+!

Julia: Passing Multiple Arguments to Anonymous Functions

In the Julia Manual under the Anonymous Functions section one of the examples that is offered is (x,y,z)->2x+y-z.
Could someone please show me how one would pass a set of arguments to this function?
Say x=(1,2,3); y=(2,3,4); z=(1,3,5).
If you define x,y and z to be arrays then you can just call the function and pass them in:
fun = (x,y,z)->2x+y-z
x=[1,2,3]
y=[2,3,4]
z=[1,3,5]
fun(x, y, z)
giving the result:
3-element Array{Int64,1}:
3
4
5
But if you want to do this with tuples, as per your example, you will need to use map:
x=(1,2,3)
y=(2,3,4)
z=(1,3,5)
map(fun, x, y, z)
this gives the same result, but this time as a tuple:
(3, 4, 5)
This is because the *, + and - operators are not defined for tuples so the formula 2x+y-z can't work. Using map gets around this by calling the function multiple times passing in scalars.
You have to assign the anonymous function to a variable, in order to call it.
julia> fun = (x,y,z)->2x+y-z
(anonymous function)
julia> fun((1,2,3),(2,3,4),(1,3,5))
ERROR: no method *(Int64, (Int64,Int64,Int64))
in anonymous at none:1
It does not work, because the tuples you set for x, does not implement the * function.

ML Expression, help line by line

val y=2;
fun f(x) = x*y;
fun g(h) = let val y=5 in 3+h(y) end;
let val y=3 in g(f) end;
I'm looking for a line by line explanation. I'm new to ML and trying to decipher some online code. Also, a description of the "let/in" commands would be very helpful.
I'm more familiar with ocaml but it all looks the same to me.
val y=2;
fun f(x) = x*y;
The first two lines bind variables y and f. y to an integer 2 and f to a function which takes an integer x and multiplies it by what's bound to y, 2. So you can think of the function f takes some integer and multiplies it by 2. (f(x) = x*2)
fun g(h) = let val y=5
in
3+h(y)
end;
The next line defines a function g which takes some h (which turns out to be a function which takes an integer and returns an integer) and does the following:
Binds the integer 5 to a temporary variable y.
You can think of the let/in/end syntax as a way to declare a temporary variable which could be used in the expression following in. end just ends the expression. (this is in contrast to ocaml where end is omitted)
Returns the sum of 3 plus the function h applying the argument y, or 5.
At a high level, the function g takes some function, applies 5 to that function and adds 3 to the result. (g(h) = 3+h(5))
At this point, three variables are bound in the environment: y = 2, f = function and g = function.
let val y=3
in
g(f)
end;
Now 3 is bound to a temporary variable y and calls function g with the function f as the argument. You need to remember that when a function is defined, it keeps it's environment along with it so the temporary binding of y here has no affect on the functions g and f. Their behavior does not change.
g (g(h) = 3+h(5)), is called with argument f (f(x) = x*2). Performing the substitutions for parameter h, g becomes 3+((5)*2) which evaluates to 13.
I hope this is clear to you.

Anonymous Scala function syntax

I'm learning more about Scala, and I'm having a little trouble understanding the example of anonymous functions in http://www.scala-lang.org/node/135. I've copied the entire code block below:
object CurryTest extends Application {
def filter(xs: List[Int], p: Int => Boolean): List[Int] =
if (xs.isEmpty) xs
else if (p(xs.head)) xs.head :: filter(xs.tail, p)
else filter(xs.tail, p)
def modN(n: Int)(x: Int) = ((x % n) == 0)
val nums = List(1, 2, 3, 4, 5, 6, 7, 8)
println(filter(nums, modN(2)))
println(filter(nums, modN(3)))
}
I'm confused with the application of the modN function
def modN(n: Int)(x: Int) = ((x % n) == 0)
In the example, it's called with one argument
modN(2) and modN(3)
What does the syntax of modN(n: Int)(x: Int) mean?
Since it's called with one argument, I'm assuming they're not both arguments, but I can't really figure out how the values from nums get used by the mod function.
This is a fun thing in functional programming called currying. Basically Moses Schönfinkel and latter Haskell Curry (Schonfinkeling would sound weird though...) came up with the idea that calling a function of multiple arguments, say f(x,y) is the same as the chain of calls {g(x)}(y) or g(x)(y) where g is a function that produces another function as its output.
As an example, take the function f(x: Int, y: Int) = x + y. A call to f(2,3) would produce 5, as expected. But what happens when we curry this function - redefine it as f(x:Int)(y: Int)and call it as f(2)(3). The first call, f(2) produces a function taking an integer y and adding 2 to it -> therefore f(2) has type Int => Int and is equivalent to the function g(y) = 2 + y. The second call f(2)(3) calls the newly produced function g with the argument 3, therefore evaluating to 5, as expected.
Another way to view it is by stepping through the reduction (functional programmers call this beta-reduction - it's like the functional way of stepping line by line) of the f(2)(3) call (note, the following is not really valid Scala syntax).
f(2)(3) // Same as x => {y => x + y}
|
{y => 2 + y}(3) // The x in f gets replaced by 2
|
2 + 3 // The y gets replaced by 3
|
5
So, after all this talk, f(x)(y) can be viewed as just the following lambda expression (x: Int) => {(y: Int) => x + y} - which is valid Scala.
I hope this all makes sense - I tried to give a bit of a background of why the modN(3) call makes sense :)
You are partially applying the ModN function. Partial function application is one of the main features of functional languages. For more information check out these articles on Currying and Pointfree style.
In that example, modN returns a function that mods by the particular N. It saves you from having to do this:
def mod2(x:Int): Boolean = (x%2) == 0
def mod3(x:Int): Boolean = (x%3) == 0
The two pairs of parens delimit where you can stop passing arguments to the method. Of course, you can also just use a placeholder to achieve the same thing even when the method only has a single argument list.
def modN(n: Int, x: Int): Boolean = (x % n) == 0
val nums = List(1, 2, 3, 4, 5)
println(nums.filter(modN(2, _)))
println(nums.filter(modN(3, _)))

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