Help with ProgressMeter?

Hello,

I am trying to implement hints given in ProgressMeter.jl to print a progressbar. I have written two toy functions (one directly copied from the hint and another one building off on the hint) but unable to understand why the first function prints the progressbar + output whereas the second function only allows me to fetch the output but does not display any progress bar. Could someone show me the correct approach? I can get the progressbars to print in the second function with @showprogress following the docs but unable to implement the instruction under β€œTips for parallel programming” for the same purpose.

#code 


@everywhere function test_bar()
 p = Progress(10, 1, "Computing function...")
 channel = RemoteChannel(()->Channel{Bool}(10), 1)

 @sync begin
    # this task prints the progress bar
    @async while take!(channel)
        ProgressMeter.next!(p)
    end

    # this task does the computation
    @async begin
        z = @distributed (+) for i in 1:10
            sleep(1)
            put!(channel, true)
            i^2
        end
        put!(channel, false) # this tells the printing task to finish
        z
    end
 end
end

@everywhere function loglike_para(beta::Array{T}, data::R1, Applications::R2, sim_draws_tau::R4,
  sim_draws_q::R5, sim_draws_eta::R6, num_draws_tau::S, num_draws_q::S, num_draws_eta::S, lambda::F, J::S,
  day_new_sampled::Array{S}, Pr_D_sampled::Array{S}, K::S, numsample::S, num_offer_samples::S, num_app_samples::S, distribution::D) where {T<:Real} where {S<:Int} where {R1<:IndexedTable, R2<:DataFrame, R4<:IndexedTable, R5<:IndexedTable, R6<:IndexedTable} where {F<:Float64} where {D<:Bernoulli{Float64}}

  ids::Array{String,2} = JuliaDB.select(data, (:std_id, :act_yr)) |>
                                     x -> IterTools.distinct(x) |> x -> table(x) |>
                                     x -> DataFrames.DataFrame(x) |>
                                     x -> Matrix(x) |>
                                     x -> convert(Array{String}, x)

  app_ids = collect(1:num_app_samples)
  p = Progress(size(ids)[1], 1, "Computing function...")
  channel = RemoteChannel(()->Channel{Bool}(size(ids)[1]), 1)

  @sync begin
     # this task prints the progress bar
     @async while take!(channel)
         ProgressMeter.next!(p)
     end

     # this task does the computation
     @async begin
        z = @distributed (vcat) for i in 1:size(ids)[1]
            sleep(1)
            std_id = ids[i, :][1]::String
            act_yr = ids[i, :][2]::String

            L_1 = L_stage1(beta, data, Applications, sim_draws_tau, sim_draws_q, sim_draws_eta,
                          num_draws_tau, num_draws_q, num_draws_eta, lambda, J, day_new_sampled, 
                          Pr_D_sampled, K, numsample, num_offer_samples, num_app_samples, distribution, std_id, act_yr, app_ids)

            L_2 = L_stage2(beta, data, sim_draws_q, num_draws_q, std_id, act_yr, day_new_sampled, 
                           Pr_D_sampled, K, J, numsample)

            L_3 = L_stage3(beta, data, sim_draws_tau, num_draws_tau, std_id, act_yr, J)

            LL = combine_all(L_1, L_2, L_3, num_draws_tau, num_draws_q, num_draws_eta)
        end
        put!(channel, false) # this tells the printing task to finish
        -sum(z)
     end
  end
end



#output 
julia> r = test_bar()
Computing function...100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| Time: 0:00:10
Task (done) @0x000000002e5dd430

julia> fetch(r)
385

julia> r_1 = loglike_para_new(beta, table(data_test), Applications, sim_draws_tau, sim_draws_q, sim_draws_eta, num_draws_tau, num_draws_q, num_draws_eta, lambda, J, day_new_sampled, Pr_D_sampled, K, numsample, num_offer_samples, num_app_samples, distribution)
Task (done) @0x000000002e5ddcd0

julia> fetch(r_1)
9.045955435747743

It seems that you are not calling put!(channel, true) inside @distributed (vcat) for i in 1:size(ids)[1].

3 Likes

Ah, yes! Thanks so much! I had been staring at it for about 30 min and didn’t spot this. I think I need some sleep :slight_smile:

2 Likes