Killing a For loop in Julia array comprehension - arrays

Question

I have the following line of code in Julia:
X=[(i,i^2) for i in 1:100 if i^2%5==0]
Basically, it returns a list of tuples (i,i^2) from i=1 to 100 if the remainder of i^2 and 5 is zero. What I want to do is, in the array comprehension, break out of the for loop if i^2 becomes larger than 1000. However, if I implement
X=[(i,i^2) for i in 1:100 if i^2%5==0 else break end]
I get the error: syntax: expected "]".
Is there any way to easily break out of this for loop inside the array? I've tried looking online, but nothing came up.

Answer 1

It's a "fake" for-loop, so you can't break it. Take a look at the lowered code below:
julia> foo() = [(i,i^2) for i in 1:100 if i^2%5==0]
foo (generic function with 1 method)
julia> #code_lowered foo()
LambdaInfo template for foo() at REPL[0]:1
:(begin
nothing
#1 = $(Expr(:new, :(Main.##1#3)))
SSAValue(0) = #1
#2 = $(Expr(:new, :(Main.##2#4)))
SSAValue(1) = #2
SSAValue(2) = (Main.colon)(1,100)
SSAValue(3) = (Base.Filter)(SSAValue(1),SSAValue(2))
SSAValue(4) = (Base.Generator)(SSAValue(0),SSAValue(3))
return (Base.collect)(SSAValue(4))
end)
The output shows that array comprehension is implemented via Base.Generator which takes an iterator as input. It only supports the [if cond(x)::Bool] "guard" for now, so there is no way to use break here.
For your specific case, a workaround is to use isqrt:
julia> X=[(i,i^2) for i in 1:isqrt(1000) if i^2%5==0]
6-element Array{Tuple{Int64,Int64},1}:
(5,25)
(10,100)
(15,225)
(20,400)
(25,625)
(30,900)

Answer 2

I don't think so. You could always just
tmp(i) = (j = i^2; j > 1000 ? false : j%5==0)
X=[(i,i^2) for i in 1:100 if tmp(i)]

Answer 3

Using a for loop is considered idiomatic in Julia and could be more readable in this instance. Also, it could be faster.
Specifically:
julia> using BenchmarkTools
julia> tmp(i) = (j = i^2; j > 1000 ? false : j%5==0)
julia> X1 = [(i,i^2) for i in 1:100 if tmp(i)];
julia> #btime [(i,i^2) for i in 1:100 if tmp(i)];
471.883 ns (7 allocations: 528 bytes)
julia> X2 = [(i,i^2) for i in 1:isqrt(1000) if i^2%5==0];
julia> #btime [(i,i^2) for i in 1:isqrt(1000) if i^2%5==0];
281.435 ns (7 allocations: 528 bytes)
julia> function goodsquares()
res = Vector{Tuple{Int,Int}}()
for i=1:100
if i^2%5==0 && i^2<=1000
push!(res,(i,i^2))
elseif i^2>1000
break
end
end
return res
end
julia> X3 = goodsquares();
julia> #btime goodsquares();
129.123 ns (3 allocations: 304 bytes)
So, another 2x improvement is nothing to disregard and the long function gives plenty of room for illuminating comments.