Code availability: user-input functions

General Usage
1

In an effort to make my main calculation code transparent to the parallelized implement, I want to have a user-defined function, then run it in parts of the calculations, doing all the setting up of parallelized calculation “invisible”. I understand I need to make the user-defined function available across cores. As a MWE:

foo.jl:

using Distributed

function p_call(func)
    ps = addprocs(2)
    r = pmap(x -> func(x), 1:4)
    rmprocs(ps)
    r
end

Use it as

include("foo.jl")

f(x) = x*im

println(p_call(f))

fails with

ERROR: LoadError: On worker 2:
UndefVarError: #f not defined

sort of expected; however, if the above is wrapped inside another function:

include("foo.jl")
function run_code()
    f(x) = x*im
    p_call(f)
end

println(run_code())

without explicitly making @everyhere f, this script works. How to best understand this and what is the preferred way to take in a user-provided function f and use it in a parallelized calculation, without exposing the parallelize setup to the user code? Thanks!