# Using addprocs and pmap inside a function

**URL:** <https://discourse.julialang.org/t/using-addprocs-and-pmap-inside-a-function/50329>\
**Category:** General Usage\
**Tags:** question\
**Created:** [November 17, 2020, 8:53pm UTC](https://discourse.julialang.org/t/using-addprocs-and-pmap-inside-a-function/50329 "2020-11-17T20:53:07Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![sdgu](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sdgu/32/19509_2.png) [@sdgu](https://discourse.julialang.org/u/sdgu)\
**Post date:** [November 17, 2020, 8:53pm UTC](https://discourse.julialang.org/t/using-addprocs-and-pmap-inside-a-function/50329/1 "2020-11-17T20:53:07Z")

</div>

Heya,

Here’s a code file `ex1.jl` that does what it’s supposed to when I run `julia ex1.jl`:

```julia
module MWE
export gen_complicated_thing, do_para

function complicated_helper()
    return Dict()
end

function gen_complicated_thing(i)
    d = complicated_helper()
    d[i] = i
    return d
end

function do_para(n, numprocs) # numprocs doesn't do anything in this example
    arr = []
    for i in 1:n
        g = gen_complicated_thing(i)
        push!(arr, g)
    end
    return arr
end
end

using .MWE
println(gen_complicated_thing(19283)) # just checking gen_complicated_thing works
println(do_para(10, 2))

```

However, I want to parallelize the `do_para` function (none of the data depends on each other, so doing so is “trivial”). If I don’t set the numprocs inside the function and didn’t want a module, I could have a file `ex2.jl`:

```julia
using Distributed
addprocs(2)

@everywhere function complicated_helper()
    return Dict()
end

@everywhere function gen_complicated_thing(i)
    d = complicated_helper()
    d[i] = i
    return d
end

function do_para(n, numprocs) # numprocs doesn't do anything in this example
    arr = pmap(gen_complicated_thing, 1:10)
    return arr
end

println(gen_complicated_thing(19283)) # just checking gen_complicated_thing works
println(do_para(10, 2))

```

But this is not what I want.

So my question is, how do I set up my module to use `addprocs` and `pmap` inside `do_para`? I have to `addprocs` before `@everywhere` right? Do I need to reload a part of the module inside `do_para` so I can `@everywhere` what I need or something? Or is there another approach using something other than `pmap`?

Edit:  
I could use `Threads.@threads` and `julia -t 2 ex1.jl` or something similar, but I would really like to specify the number of threads/processes inside the function.

```julia
function do_para(n, numprocs) # numprocs doesn't do anything in this example
    arr = Array{Any}(undef, n)
    Threads.@threads for i in 1:n
        g = gen_complicated_thing(i)
        arr[i] = g
    end
    return arr
end

```