Hi!
I decided to create my very first package. This “baby” package contains only one function (I give an example):
using Plots
using Distributions
function easy(x::Vector{Float64})
a = print("The mean is:", mean(x))
b = print("\nThe variance is:", var(x))
c = plot(x)
end
The user gives
a=[1,5,4,7.6]
easy(a)
Then, the function prints the mean of a, the variance of a and a simple plot of a. I get some functions from the Distributions.jl package and the plot from the Plots.jl package. I have followed all the needed steps to create my package and it’s time to test it.
I found a simple function test example:
using MyPackage
using Test
@testset "MyPackage" begin
x = 2
y = 2
@test MyPackage.sum(x,y) = = 4
end
This is true, so the test is passed. In this case, it’s logical to test this.
In my case, I didn’t create any mathematical or new complex structured functions to test; only a function that prints some statistical results and an output of a plot (this might help a student).
In my case, though, what do I need to test my function? Does it make any sense?
I don’t know of a way to do this with the standard library, but there are two packages that can help by capturing the output of your function to a string which you can then test against an expected result:
https://github.com/JuliaDocs/IOCapture.jl
https://github.com/JuliaIO/Suppressor.jl
Thank you! But what do I test here? My easy() function or every print separately? The type of easy(a) is Plots.Plot{Plots.GRBackend} because the prints are only prints. See the screenshot below:

It is probably worth looking at the tests for plots.jl https://github.com/JuliaPlots/Plots.jl/tree/master/test to see what you can query about a plot once it has been created. Then you can decide which of those attributes are important to your function and ensure they match the expected value.
If you return the values in the function, can can test them. Here is an example:
function easy(x::Vector{Float64})
μ = mean(x)
σ = std(x)
print("The mean is:", μ)
print("\nThe variance is:", σ)
c = plot(x)
return μ,σ,c
end
x = [1.0,2.0,3.0]
μ,σ,p = easy(x)
@test μ ≈ 2.0
@test σ ≈ 1.0
@test p[1][1][:y] == x
I’m not sure how to test the print statements and plot further.
As contradict suggested, you can test the print statement like so:
using IOCapture
c = IOCapture.capture() do
easy(x)
end
@test c.output == "The mean is:2.0\nThe variance is:1.0"
Thanks to both of you! It worked like a charm! 
Can’t you just use redirect_stdout for this?
Extra credit: Functions that print things to stdout typically define two methods like this
function myfun(io::IO, x)
println(io, 3x)
end
myfun(x) = myfun(stdout, x)
Testing this function is easier, because we can use our own IOBuffer instead of stdout.