Array comprehension

Basic Syntax

Julia's array comprehensions use the following syntax:

[expression for element = iterable]

Note that as with for loops, all of =, in, and are accepted for the comprehension.

This is roughly equivalent to creating an empty array and using a for loop to push! items to it.

result = []
for element in iterable
    push!(result, expression)

however, the type of an array comprehension is as narrow as possible, which is better for performance.

For example, to get an array of the squares of the integers from 1 to 10, the following code may be used.

squares = [x^2 for x=1:10]

This is a clean, concise replacement for the longer for-loop version.

squares = []
for x in 1:10
    push!(squares, x^2)

Conditional Array Comprehension

Before the Julia 0.5, there is no way to use conditions inside the array comprehensions. But, it is no longer true. In Julia 0.5 we can use the conditions inside conditions like the following:

julia> [x^2 for x in 0:9 if x > 5] 
4-element Array{Int64,1}:

Source of the above example can be found here.

If we would like to use nested list comprehension:

julia>[(x,y) for x=1:5 , y=3:6 if y>4 && x>3 ]
4-element Array{Tuple{Int64,Int64},1}:

Generator Comprehensions

Generator comprehensions follow a similar format to array comprehensions, but use parentheses () instead of square brackets [].

(expression for element = iterable)

Such an expression returns a Generator object.

julia> (x^2 for x = 1:5)

Function Arguments

Generator comprehensions may be provided as the only argument to a function, without the need for an extra set of parentheses.

julia> join(x^2 for x = 1:5)

However, if more than one argument is provided, the generator comprehension requries its own set of parentheses.

julia> join(x^2 for x = 1:5, ", ")
ERROR: syntax: invalid iteration specification

julia> join((x^2 for x = 1:5), ", ")
"1, 4, 9, 16, 25"

Multidimensional array comprehensions

Nested for loops may be used to iterate over a number of unique iterables.

result = []
for a = iterable_a
    for b = iterable_b
        push!(result, expression)

Similarly, multiple iteration specifications may be supplied to an array comprehension.

[expression for a = iterable_a, b = iterable_b]

For example, the following may be used to generate the Cartesian product of 1:3 and 1:2.

julia> [(x, y) for x = 1:3, y = 1:2]
3×2 Array{Tuple{Int64,Int64},2}:
 (1,1)  (1,2)
 (2,1)  (2,2)
 (3,1)  (3,2)

Flattened multidimensional array comprehensions are similar, except that they lose the shape. For example,

julia> [(x, y) for x = 1:3 for y = 1:2]
6-element Array{Tuple{Int64,Int64},1}:
 (1, 1)
 (1, 2)
 (2, 1)
 (2, 2)
 (3, 1)
 (3, 2)

is a flattened variant of the above. The syntactic difference is that an additional for is used instead of a comma.

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